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International Journal of Industrial and Systems Engineering

International Journal of Industrial and Systems Engineering (IJISE)

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International Journal of Industrial and Systems Engineering (122 papers in press)

Regular Issues

  • Stability Analysis of Asynchronous Switched Positive Systems with Unstable Subsystems   Order a copy of this article
    by Jingjing Hu, Pingping Gu, Huiwen Liu, Dexiang Liu 
    Abstract: This paper investigates the stability problems of asynchronous switched positive systems based on mode-dependent average dwell time method in continuous-time context. While using mode-dependent average dwell time to study the stability of switched systems, each subsystem must be stable, otherwise a state feedback controller should be designed for the unstable subsystem. But in practical application, when the subsystem is activated one by one, it usually takes a period of time to identify which one of the state feedback controllers should be activated, which causes the asynchronisation. Next, in consideration of the difficulty of designing an appropriate state feedback controller for some unstable subsystems, this paper is aimed at obtaining the stability condition of asynchronous switched positive systems with both stable and unstable subsystems.
    Keywords: asynchronization; mode-dependent average dwell time; stabilization; switched positive systems; unstable subsystem.
    DOI: 10.1504/IJISE.2020.10016058
  • Assessment of human and system related barriers during implementation of Green Leagile Six Sigma (GLSS) in Indian manufacturing industries   Order a copy of this article
    by NAVEEN VIRMANI, Urmi Ravindra Salve 
    Abstract: There is a radical change at level of competition during past few years in manufacturing industries. Today, the customer desire high quality products at economical price and that too in minimum span of time. So, it is required for industries to adopt manufacturing strategies in compliance with customer requirements and preferences. Also, there is a need of using greener technologies to manufacture products. Therefore, it is imperative to produce economical products quickly while maintaining quality norms (ISO, OHSAS etc). Industries are required to adopt state-of-art technology, methods and research strategies to compete in the global market. In this paper, concept of Green Leagile Six Sigma has been discussed and human factors and system related barriers had been identified through literature review. Exploratory factor analysis (EFA) technique used to categorize the attributes into constructs. Also, Confirmatory factor analysis (CFA) was used for model fit.
    Keywords: GLSS; Agile; Green; EFA; CFA; Lean; Six Sigma.
    DOI: 10.1504/IJISE.2020.10029483
  • Demand-Supply Planning and Sustainability Aspect for Agro-based Perishables in Cold-chain   Order a copy of this article
    by AMAN BHATNAGAR, Prem Vrat, Ravi Shanker 
    Abstract: The primary objective of this paper is to: (i) determine the optimum storage requirements for agro-based perishables using production and distribution planning model to absorb the demand fluctuations in an economic manner, encouraging inter-state transportation of perishables so that available infrastructure is utilized efficiently, (ii) determine the cost variation along the potato value chain from farm to fork (iii) analysing the cost of building cold storage, (iv) focus on the sustainability aspect of cold-chain in order to have better utilisation of the cold storages and logistics, thereby reducing food loss and carbon footprints (v) determine the payback period of the investment made, Profit & Loss (PnL), Un-discounted rate of return, Earnings before interest, taxes, and amortization (EBITA) Margins, Profit After Tax (PAT), projected balance sheet and depreciation schedule.
    Keywords: cold-chain; cold storage; potato value chain; inter-state trade; transportation; logistics distribution and perishable agri-value chain.
    DOI: 10.1504/IJISE.2020.10029563
  • Production Lead Time Improvement through Lean Manufacturing   Order a copy of this article
    by Sisay Geremew Gebeyehu, Amdework Gochel, Muluken Abebe 
    Abstract: The aim of this research was to improve the production lead time by minimizing different wastes which does not add value on final product. First, the current production floor and layout has been studied and mapped using Value Stream Mapping and Spaghetti Diagram is applied to identify manufacturing wastes. Next, lean manufacturing techniques have been deployed to improve the bottleneck areas. The result shows that production lead time was reduced by 23.66%, process cycle efficiency was improved 8.6%, Work in Process (WIP) time reduced by 25.59%, non-value adding time (waiting time) reduced by 37.74%, total distance traveled reduced by 61.2% and the number of workers reduced by 9. Finally, it was concluded that the research has significant benefit for Hibiret Manufacturing & Machine Building Industry (HMMBI) and similar manufacturing industries.
    Keywords: Lead time; lean manufacturing; value stream map.
    DOI: 10.1504/IJISE.2020.10029891
  • A maintenance optimization approach based on genetic algorithm for multi-component systems considering the effect of human error   Order a copy of this article
    by Hagag Maher, Mohamed F. Aly, H. Afefy Islam, Tamer Abdelmaguid 
    Abstract: The total maintenance cost can be reduced by grouping maintenance actions of several components. This paper contributes to the existing literature by introducing an enhanced maintenance optimization approach that considers the effect of maintenance crew loading due to grouping on the maintenance decisions of multi-component systems. A modified mathematical model is firstly developed for evaluating the failure probability function of each component, the remaining useful life and the maintenance cost. Economic and structural dependencies are taken into consideration. A simulation is secondly implemented to provide estimates of the associated costs with changes in the decision variables. Using the simulation model, an optimization approach based on a genetic algorithm is thirdly developed to minimize the long-term mean maintenance cost per unit time. Computational results show that the proposed maintenance optimization approach provides considerable maintenance cost savings and emphasizes the importance of considering the effect of maintenance crew constraints in maintenance scheduling.
    Keywords: Maintenance grouping; multi-component systems; genetic algorithm; maintenance human constraints; maintenance process simulation.
    DOI: 10.1504/IJISE.2020.10030489
  • Robust Simultaneous Lot-sizing and Scheduling with considering Controllable Processing Time and Fixed Carbon Emission in Flow-shop Environment   Order a copy of this article
    by Mehdi Bijari, Milad Mirnajafi Zadeh 
    Abstract: A new robust model is presented for simultaneous lot-sizing and scheduling problem in a flow-shop environment with controllable processing time in this study. In view of the importance of carbon emissions in green production, this model takes account of limitations in this respect. Different speeds of machines can also affect production, back order, inventory holding costs, scrap rates, as well as carbon emissions. In the present study, a new model is proposed under certainty and uncertainty. In order to deal with uncertainty, robust optimization is employed. The robust model in this study is in non-deterministic polynomial-time (NP) hardness complexity class; therefore, a total of five heuristic algorithms are introduced based on Fix-and-Relax (F&R) and Fix-and- Optimize (F&O) approaches to solve larger instances. In conclusion, the results obtained from the algorithms based on F&O are given higher quality solutions compared with those based on F&R heuristic.
    Keywords: Simultaneous Lot-Sizing and Scheduling; Controllable Processing Time; Carbon Emission; Robust Optimization; Fix and Optimize.
    DOI: 10.1504/IJISE.2020.10030630
  • Optimal Pricing for Ride Sharing   Order a copy of this article
    by XIANGYING CHEN, Yongzhong Wu, Yuxin Lu, Yongwu Zhou 
    Abstract: The ride sharing business has developed rapidly in recent years. The pricing of the ride sharing service is critical for the profitability of the operators. Pricing too high may reduce passenger demand, and hence increase detours and distance, while pricing too low may reduce the revenue. In order to analyze the dynamics of optimal pricing, a mathematical model is developed to maximize the total profit.In the model, the higher-level pricing decision depends on the lower-level order assignment and routing problem.Numerical experiments with the model show that the operator does not necessarily benefit from providing the ride sharing option. The pricing of ride sharing is critical for profitability. When the total travel demand is high (e.g., in peak hours), the operator should adopt a lower relative pricing in order to maximize profit.
    Keywords: Ride sharing; optimal pricing,vehicle routing problem; choice model; order assignment.
    DOI: 10.1504/IJISE.2020.10030703
  • An analytical study on establishing strategies for improving the productivity of the spinning industries   Order a copy of this article
    by Ismail W. R. Taifa, Ibrahim Joseph Mwasubila, Beatus A. T. Kundi 
    Abstract: Strategies for improving the productivity of the spinning industries are much needed. In this paper, a case of a spinning industry was systematically studied. The strategies for enhancing productivity were established through a mixed approach. The studied industry experienced low productivity as they were only achieving 55%68% of their production plan. Also, their actual operational machine availability was 67%. The proposed strategies include improving the spooling and the drawing process by installing new machinery technology; improve raw materials and components flow; hiring well-trained workers; develop employee training programs; search for new market segments; establish effective information and communications technology section, and develop an implementable maintenance plan. The study also revealed that system dynamics modelling helps to arrange descriptive information analytically. Thus, Vensim software was applied to illustrate the 2 I.J. Mwasubila et al. differences between productivity, specifically before and after implementing the established strategies. The study considered only a single industry and single-factor productivity measures.
    Keywords: productivity improvement; productivity index; single-factor productivity; multifactor productivity measures; strategies; competitive strategy; system dynamics; Vensim software; spinning mill.
    DOI: 10.1504/IJISE.2020.10030901
  • Optimization of multiobjective supply chain networks considering cost minimization and environmental criteria   Order a copy of this article
    by John Wilmer Escobar, Natalia Segura Rosas, Juan Camilo Paz Roa 
    Abstract: This article considers the optimisation problem of a multi-objective mass-consumption supply chain network considering cost minimisation and environmental criteria, as well as the analysis of scenarios with variable demand. This study seeks to determine the closure and consolidation of distribution centres and the identification of product flows in the network. The efficiency of the mathematical model has been tested with real information obtained from a Colombian multinational company manufacturing products of mass-consumption. The results confirm the efficiency of the model and its positive impact on determining the environmental impact of gas emissions related to the type of transportation used and the appropriate cost for the case study company.
    Keywords: Network Optimization; Multiobjective Mathematical Model; Total Cost; Environmental Impact; Logistics; Scenario Analysis.
    DOI: 10.1504/IJISE.2020.10030916
  • Agent-Based Heuristics Model for Measuring Customer Disruption Impact on Production and Inventory Replenishment   Order a copy of this article
    by Ammar Al-Bazi, Tunde Adediran 
    Abstract: Agent-based simulation approach in production and inventory environment is capable of responding and adapting to disruptions caused by customers’ changing requirements. The impacts of disruptions in production and inventory systems can be measured through learning and decision-making ability of system agents. In this paper, agent-based modelling integrated with heuristic optimisation approach is presented as embedded within a scheduling and rescheduling framework. The proposed approach is implemented in a disrupted OEMs parts manufacturing system. The integration of the framework modules in connection with inventory control helped production planners to manage disruptions by tracking order processing times and quantities and for performance measurement. The proposed approach is compared with the few existing related methods like the sequential method. The proposed approach not only revealed the impact of disruptions in terms of process times and order quantities but offered 'available times' which were applied for production support and inventory replenishment. This demonstrates a valuable and viable resolution strategy responding and adapting to disruptions caused by customers.
    Keywords: Customer Disruption Impact; OEM Environment; Production scheduling; Inventory Replenishment; Agent-Based Simulation; Heuristics Optimisation.
    DOI: 10.1504/IJISE.2020.10031323
  • An overview of industry 4.0 in manufacturing industries   Order a copy of this article
    by Dheeraj Nimawat, B. Gidwani 
    Abstract: In the current scenario, manufacturing industries are rapidly moving towards customized production from mass production to meet the current market competition. Industry 4.0 prompts the digitalization time. Industry 4.0 emphasizes intelligent products, potential customers, and change of industrial machine suits. It is interconnected inside the advanced and innovative view with the comparing virtual portrayal. Industry 4.0 inventiveness has engaged an impressive concentration of industries and researchers. This paper comprises study of 164 reputed research papers and addresses evolution of Industry 4.0, key technologies, initiatives by various nations in this era, review of empirical analysis on Industry 4.0, and presented future scope in the area of Industry 4.0 regarding survey of barriers to adopt Industry 4.0, maturity of Industry 4.0 concept and impact of key technologies of Industry 4.0 in the today’s scenario. This paper will help to the existing and future industries, and researchers in the context of Industry 4.0.
    Keywords: Industry 4.0; Big Data; Autonomous Robots; Simulation; Additive Manufacturing; Industrial Internet of Things; Augmented Reality; Cyber Physical Systems; Fourth Industrial Revolution.
    DOI: 10.1504/IJISE.2020.10031375
    by Neeta Sharma, Prem Vrat 
    Abstract: This paper presents an analysis of exploratory survey conducted to investigate the consumers’ perception by using the instrument of structured questionnaire about stock-induced consumption of various commodities which would invariably result in resource wastage. The intended outcome of this survey is to find out the stock-induced consumption index of these commodities which exhibit behavioural tendencies of different consumers. This would eventually be used by inventory control practitioners to estimate the shape parameter (?) of these commodities because parameter estimation is identified as the major limitation resulting in poor applicability of the stock-dependent demand inventory models. In addition, this paper attempts to classify these commodities on the basis of their high, medium and low potential for stock-induced consumption (HML analysis) to facilitate use of resources to their maximum efficiency by concentrating on items having the greatest potential for wasteful consumption. Perishability is considered as one of the driving forces in stock-induced consumption
    Keywords: stock-dependent demand; stock-induced consumption index; perishability index; HML analysis; behavioural inventory management.
    DOI: 10.1504/IJISE.2020.10031937
  • Minimizing Makespan of Batch Processing Machine with Unequal Ready Times   Order a copy of this article
    by Leena Ghrayeb, Shanthi Muthuswamy, Purushothaman Damodaran 
    Abstract: This research considers scheduling a single batch processing machine at a contract electronics manufacturer. The processing times, ready times and the sizes of the jobs are given and the total size of the batch should not exceed the machine capacity. The batch ready time is equal to the latest ready time of all the jobs in the batch. The objective is to minimize the makespan. The commercial solver used to solve the mathematical formulation proposed requires long run times. Consequently, several heuristics and lower bounding procedures are proposed. Through an experimental study, it is shown that one of the lower bounds is within 40% of the best known integer solution from CPLEX for the 200-job instances. The heuristics are very effective in finding good quality solutions with short run times. For smaller problem instances, the quality of the heuristic solution is within 10% of the best known solution from CPLEX.
    Keywords: Batch Processing Machine; Scheduling; Makespan; Heuristics; Lower bound.
    DOI: 10.1504/IJISE.2020.10032044
  • A Simulated Annealing Approach to Minimize Makespan in a Hybrid Flowshop with a Batch Processing Machine   Order a copy of this article
    by Santha RajaKumari Upadhyayula, Shanthi Muthuswamy, Purushothaman Damodaran 
    Abstract: A two-stage hybrid flowshop with a batch processing machine (BPM) in stage 1 and a set of discrete processing machines in stage 2 is considered in this research. Job sizes and their processing times are given. The BPM can process multiple jobs simultaneously as long as the total size of all jobs does not exceed its capacity, and the processing time is dictated by the longest processing job in the batch. In stage 2, the jobs have to be processed one at a time. The objective is to minimise the makespan. As the problem under study is NP-hard, a simulated annealing (SA) algorithm was designed. A mathematical formulation was also developed and a commercial solver was used to solve the problem instances. An experimental study was conducted to compare SA with the solver. The study highlights the efficiency of SA in solving larger problem instances with good quality solution in shorter computational time.
    Keywords: batch processing machines; BPMs; scheduling; hybrid flowshop; simulated annealing; makespan; heuristics.
    DOI: 10.1504/IJISE.2020.10032492
  • A multi-strategy integration Pareto based artificial colony algorithm for multi-objective flexible job shop scheduling problem with the earliness & tardiness criterion   Order a copy of this article
    by Boxuan Zhao, Jiao Zhao, Yulei Gu, Jingshuai Yang 
    Abstract: This paper studies the multi-objective flexible job shop scheduling problem with the earliness and tardiness (E&T) criterion, explores the decoding and search strategies of algorithms under the coexistence of the mean E&T and makespan, and provides a makespan-constrainted three-phase decoding mechanism and local search strategies for both of them. Referencing to the flexibility of the artificial bee colony algorithm framework, multiple strategies are integrated properly in the algorithm to realise simultaneous optimisation of regular and irregular objectives. Through testing six benchmark instances of different scales with tight or loose delivery time for jobs, the distribution characteristics of the Pareto optimal solution set of the collaborative optimisation of the mean E&T and the makespan are explored. The proper integration of various search strategies can make the proposed algorithm have better performance.
    Keywords: flexible job shop scheduling; just-in-time delivery; earliness and tardiness; E&T; multi-objective; artificial bee colony.
    DOI: 10.1504/IJISE.2020.10032843
  • Applying cross efficiency evaluation methods for multi-objective emergency relief supply chain network model   Order a copy of this article
    by Jae-Dong Hong 
    Abstract: This paper studies a multi-objective emergency relief supply chain network (ERSCN) model, which would play a critical role in providing disaster relief items in time Data envelopment analysis (DEA) method is applied to identify efficient ERSCN schemes among the proposed schemes To overcome the weakness of the traditional or classical DEA method, a cross-efficiency (CE) evaluation method was proposed to improve DEA’s poor discriminating power But the original CE method also reveals its own weaknesses. So, the three CE methods, called Aggressive, Benevolent, and Neutral methods, are proposed to complement the shortcomings of DEA and CE DEA methods. This paper proposes a process of applying these CE evaluation methods in DEA for designing the ERSCN system Through a case study, the applicability of the proposed process is demonstrated, and it performs well regarding identifying the efficient ERSCN systems and can be used as an important tool to design various supply chain network schemes efficiently and effectively.
    Keywords: Data Envelopment Analysis; Cross Efficiency Evaluation; Emergency Supply Chain Network.
    DOI: 10.1504/IJISE.2020.10033187
  • A Novel Urban Road Management System Based On Data Mining   Order a copy of this article
    by Guanlin Chen, Jiapeng Shen, Min Li, Min Jiang 
    Abstract: With the accelerating process of urbanization in China, new problems and challenges have also emerged in the management of urban roads. In order to apply the data analysis technology to the above problems, we propose a combined forecasting model which can help us to forecast the number of daily cases that will happen in a region over the next few days. Our experimental results show that this model has better predictive ability than other models and can be applied to a variety of situations. What’s more, in order to apply the model to real life, we also develop a novel urban road management system(NURMS) which realizes some useful functions such as prediction of the number of daily cases, inquiry of daily cases, and statistical analysis of historical data. We believe our work will bring effective data support to the management of urban roads.
    Keywords: data mining; SVR; BP; ARIMA; urban road management.
    DOI: 10.1504/IJISE.2020.10033539
  • Social Commerce Constructs and Consumers' Purchase Intention from Minimalist Brands   Order a copy of this article
    by Hadi Zare, Zhan Su, Hooman Abdollahi 
    Abstract: The social media and online communities have established new platforms for e-commerce by engaging both consumers and corporations in producing new product or services. Moreover, individuals interaction on the cyberspace has evolved e-commerce towards social commerce. On the other hand, business incorporations have found the use of minimalism application in designing, which removes unnecessary aspects, attracts more audience. Therefore, drawing on literature the authors propound a new adopted model to portray a more transparent vision of social commerce. To examine the relationships among the model constructs, an empirical study was organised for this purpose, a survey was designed. In doing so, SEM methodology structural equation modelling (SEM) has been used with Smart PLS 3 software in order to confirm or reject assumptions in the present study is employed to gauge the proposed model.
    Keywords: Social Commerce Construct; trust; Purchase Intention; Minimalist Brand; Brand loyalty.
    DOI: 10.1504/IJISE.2020.10033667
  • Research On Operation And Maintenance Management Risk Assessment Of Power Communication Network Based On Dematel   Order a copy of this article
    by Youxiang Zhu, Anqi Tian, Zhenyu Lu, Si Jie Zhan, Xiaoyong Wang 
    Abstract: In order to overcome the low accuracy problem of operation and maintenance risk assessment of power grid communication network, this paper proposes a method for operation and maintenance management risk assessment of power communication network based on DEMATEL, which describes the pedigree, business bearing and network association, and analyzes the pedigree of power communication network based on DEMATEL from the perspective of the whole network and subnet, to obtain the point what should be paid attention to in the process of risk assessment. The experimental results show that the accuracy of risk assessment method is close to 100%, and the failure rate is less than 3%, which improves the early warning rate, so that the accuracy of risk assessment, risk assessment rate and early warning rate of operation and maintenance management of power communication network have been improved.
    Keywords: DEMATEL; Power communication network; Operation and maintenance; Risk assessment.
    DOI: 10.1504/IJISE.2020.10033800
  • Conceptual design of Ergonomic Food truck using QFD-GRA-DSM Hybrid methodology   Order a copy of this article
    Abstract: As the competition among the food truck business entrepreneurs is growing rapidly in India, food truck owners have to capture the tastes of the consumers from time to time, maintain trained staff for food preparation, create healthy, hygienic environment, ensure quality in service etc. In addition to these, the effective utilization of limited kitchen space to meet all the requirements is essential. In this context, ergonomic intervention in designing kitchen space of the food truck is one of the prime considerations. In this paper, a methodology is developed by using Quality Function Deployment (QFD), Grey relational analysis (GRA) and Design structure matrix method (DSM) for conceptual design of ergonomic food truck with a view to deploy the requirements of users in to the design of kitchen portion of the food truck. The proposed methodology is demonstrated through a case study in this paper.
    Keywords: conceptual design of a product; ergonomics; ergonomic food truck; quality function deployment; grey relational analysis; design structure matrix method.
    DOI: 10.1504/IJISE.2020.10033802
  • Research On High-Speed Motion Control Of Green Environmental Protection Production Line For High-Speed Flexible Cartridge Packing   Order a copy of this article
    by Kuiwu Liu 
    Abstract: In order to overcome the poor track control performance of the production line motion control method, a high-speed motion control method of green environmental protection production line with high-speed flexible box packing is proposed. This method obtains the speed constraint conditions according to the speed connection between the path segments, carries out the speed preprocessing between the path segments, introduces the polynomial quintic interpolation algorithm, plans and generates the motion trajectory, obtains the speed control curve of the production line, implements the path planning, constructs the high-speed motion control model of the production line, and realises the high-speed motion control of the production line. The experimental results show that the interruption of the trajectory control line is the smallest, the controller tends to be stable for 2 s, and the packaging error can be controlled within
    Keywords: High-speed flexible cartridge; Packing; Green production line; High-speed motion control;.
    DOI: 10.1504/IJISE.2020.10033886
  • A Holistic Perspective of the Sustainable Manufacturing: A Novel Conceptual Approach   Order a copy of this article
    by Ibrahim Garbie, Abdelrahman Garbie 
    Abstract: Sustainability is recently considered the buzzword in manufacturing enviornments Analysis and investigation of sustainability in manufacturing becomes urgent not only from one stream but also from the whole manufacturing streams The main goal of this paper is to explain how to classify sustainability in all streams of manufacturing as a whole (machine components design, manufacturing processes, and manufacturing systems) through identifying the sustainability enablers A framework to analyze the whole manufacturing streams will be illustrated and discussed to identify which enablers are significant in each manufacturing stream and which manufacturing stream is more significant towards whole manufacturing sustainability than others A novel assessment for measuring the manufacturing sustainability will be presented It seemed that the stream of the manufacturing system represented the highest turbulent one due to the diversity and numerous sustainable enablers It was also observed from this analysis and investigation that understanding sustainable manufacturing as a whole is
    Keywords: sustainable manufacturing; sustainability/sustainable development; manufacturing process; manufacturing systems; and machine design.
    DOI: 10.1504/IJISE.2020.10033957
  • Prognosis of failures due to the abnormal temperature increase of the malt crusher, using ANFIS neuro-fuzzy approach: case study of the flour mill of the breweries of Cameroon   Order a copy of this article
    by Sandra NZENEU, KOMBE Timothée 
    Abstract: In this article, we present a method for predicting malt grinder failures. The objective is to control the evolution of the temperature of the grinding chamber, in order to optimise the availability and reliability of the grinder. The methodological approach is based on the ANFIS neuro-fuzzy network, which offers, in a single tool, precision for non-linear systems. The predicted temperature is classified according to a mode of operation of the equipment. The evaluation of the performance of the prediction and classification systems is characterised respectively by a learning error function of 0.1236 and a classification rate of 79.6%.
    Keywords: Artificial Intelligence; Hybrid neuro-fuzzy network; Form recognition; Failure; Prognosis.
    DOI: 10.1504/IJISE.2020.10034130
  • Identifying and classifying sustainable supply chain performance indicators: a GRI based multivariate analysis   Order a copy of this article
    by Arash Shahin, Ali Goharshenasan, Abbas Sheikh Aboumasoudi 
    Abstract: This study aims to identify and classify the performance indicators of a sustainable supply chain based on the Global Report Initiative (GRI) standard using multivariate analysis. Marjan Tile Company has been selected for the case study. Performance indicators of the sustainable supply chain have been reviewed and the GRI standard has been selected. Then, the value of each indicator has been measured using a questionnaire filled by the experts of the company. In the next step, the data has been analysed using multivariate analysis and principal component analysis (PCA). Findings on the classification of performance indicators indicated that human rights varied from nine sub-dimensions to three indicator clusters, and the indicators relevant to social dimensions of society scope and social scope of product liability varied from five sub-dimensions to three indicator clusters, implying the maximum and minimum variation of the clusters.
    Keywords: Sustainable Supply Chain; Multivariate analysis; Social dimension; GRI standard; Ceramic and tile industry.
    DOI: 10.1504/IJISE.2020.10034312
  • Optimization of tensile and compressive behavior of PLA 3-D printed parts using Categorical Response Surface methodology   Order a copy of this article
    by Muhammad Abas, Muhammad Waseem, Tufail Habib, Usman Ghani, Muhammad Alam Zaib Khan, Qazi Muhammad Usman Jan 
    Abstract: Additive manufacturing is gaining momentum in different industries to fabricate complex parts in a short period. However, the fabrication of quality parts with required mechanical strength greatly depends on printing process parameters. So the present study aims to optimize process parameters of 3-D printed Polylactic Acid (PLA) part of improving mechanical strength, namely tensile and compression strength using Response Surface Methodology (RSM). The input printing process parameters are layer height, infill percentage, raster width and infill patterns (i.e. linear, hexagonal and diamond), while the responses are tensile and compressive strengths. Box Behnken array design is applied for experimental runs and also to fit quadratic regression models. Three levels are set for each printing process parameters i.e. layer height (0.1, 0.2, 0.3mm), infill percentage (10, 55,100), raster width (0.4, 0.45, 0.5mm) and infill pattern type (linear, hexagonal, diamond). Effect of printing process parameters on responses are studied using Analysis of variance.
    Keywords: Additive manufacturing; fused deposition modelling; 3D printing; Poly-lactic acid; tensile strength; compression strength; analysis of variance; Response surface methodology.
    DOI: 10.1504/IJISE.2020.10034682
  • A Multi-Level Green Reverse Logistics Network Design for Single Manufacturer and Integration of Return Distribution Warehouses in Supply Chain Management   Order a copy of this article
    by Mohammad Reza Shahraki, Shima Shirvani 
    Abstract: This study develops a linear programming model in a closed loop supply chain network including supply, production, distribution, collection, recycling and disposal centres taking into account variables of route, vehicle and volume of the vehicle. Multilevel and multi-product modes are also considered for single manufacturer and integration of return distribution warehouses and processing costs are also taken into account in locations. All modifiable returned goods are shipped to production and distribution centres to be provided to the consumer directly in the logistics process. The purpose of the model is to reduce costs of the green reverse logistics network. The proposed model reduces the cost of transportation according to the vehicle and the route and vehicle size and ultimately reduces the costs of reverse logistics network distribution. An example is reviewed for validation of the proposed model and finally general conclusions are presented. The results show that the proposed model is able to determine the best route, type of vehicle and shipping volume and in the reverse logistics network.
    Keywords: reverse logistics; supply chain; return distribution cost; returned products.
    DOI: 10.1504/IJISE.2020.10034937
    by Ajith Tom James  
    Abstract: Availability of automobiles in fleet service is very crucial and is often influenced by the maintenance. Generally, bus fleet organisations have got their own garage facilities. However, the maintenance performance levels of garages need not to be the same with all organisations and locations. Hence, a measurement system is necessary to evaluate the maintenance performance of garages for corrective actions. This paper develops a framework for maintenance performance measurement (MPM) based on MPIs specific to the objectives of fleet service maintenance garages based on hybrid methodology that is a combination analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The hybrid methodology is applied for comparing maintenance performance of garages of four different municipal bus fleet services in India. The novelty of this paper includes development of MPIs specific to garages of bus fleet and comparison of the fleet garages based on maintenance performance.
    Keywords: fleet service garage; maintenance performance measurement; MPM; analytic hierarchy process; AHP; TOPSIS.
    DOI: 10.1504/IJISE.2020.10035036
  • Availability analysis using Markovian approach and Maintenance Planning of a process industry   Order a copy of this article
    by Nitin Panwar, SANJEEV KUMAR 
    Abstract: In the present paper, a probabilistic method for stochastic modelling and performance evaluation of a pulping unit is suggested. The paper plant consists of various units like feeding, pulping system, bleaching system, screening system and paper production system. Pulping unit is one of the paper plant’s most significant functional units, consisting of five repairable subsystems which are arranged in series. Using Markov process, differential equations are created after drawing transition diagram and these models are then used to discover the pulping unit’s availability by considering the repair and failure information acquired from maintenance personnel. Based upon the various performance values for critical system using analytic hierarchy process (AHP), first the priority weights of the considered criteria are found and ranking of failure causes are performed using vlse kriterijumska optimizacija kompromisno resenje (VIKOR) to find the most critical component.
    Keywords: Markovian; stochastic modelling; multi-criteria decision making; MCDM; availability; AHP-VIKOR; maintenance planning.
    DOI: 10.1504/IJISE.2020.10035038
  • Yield-level performance of quality dimensions trough T2 charts and multivariate capacity indicators applied to a fumigation services company   Order a copy of this article
    by Tomás Fontalvo, Roberto Herrera, Yulibeth Gonzales 
    Abstract: This research provides a yield-level performance of quality dimensions trough a T-squared control chart and a multivariate capacity indicator to assess the dimensions of the fumigation service. Six Sigma concepts, control charts and multivariate capability indicators were used as the theoretical basis. The research was evaluative, for which all the information regarding the quality dimensions was evaluated in 11 periods of 2019, for which the primary sources associated with the records generated by the fumigation services company were used. As results, the yield level performance was excellent; and the multivariate control chart shows variability in the quality dimensions in the analysed periods; and the multivariate capacity indicator makes it possible evaluate punctually and globally the service quality, showing a good performance. A three-phase method is proposed that allows to evaluate the service dimensions through a periodic, global, longitudinal and multidimensional perspective to guarantee the sustainability of the service quality.
    Keywords: service quality; Six Sigma in service; multivariate control charts; multivariate capability indicators; fumigation services.
    DOI: 10.1504/IJISE.2020.10035051
  • A Single-Stage Batch Scheduling Model with m Heterogeneous Batch Processors Producing Multiple Items Parts Demanded at Different due dates.   Order a copy of this article
    by Nita Puspita Anugrawati Hidayat, Wisnu Aribowo, Abdul Hakim Halim, Andi Cakravastia 
    Abstract: This research deals with a batch scheduling problem to minimise total actual flowtime of parts through the shop with m heterogeneous batch processors, i.e., the machine simultaneously processing all parts in a batch. The parts to be processed are multiple items, and the completed parts must be delivered at different due dates. The total actual flow time of parts can be defined as an interval between arrival times of the parts and their respective due dates. The objective of minimising the total actual flowtime is not only to satisfy the due dates as a commitment to the customers, but also to minimise the length of total time spent by the parts in the shop. The problem is formulated as a mathematical model and an algorithm to solve the problem is proposed. Numerical examples show that the proposed algorithm can effectively solve the problem.
    Keywords: batch scheduling; batch processor; actual flowtime.
    DOI: 10.1504/IJISE.2020.10035054
  • Accurate medical information recommendation system based on big data analysis   Order a copy of this article
    by Xi Chen, Jieru Wang 
    Abstract: In order to solve the problems of low recommendation accuracy and long response time in traditional medical information recommendation system, a medical information accurate recommendation system based on big data analysis is proposed. The system is designed as medical information data acquisition module, medical information storage module and medical information accurate recommendation module. In the medical information data acquisition module, crawler technology is used to obtain medical information data, association rule algorithm is used to mine the medical information data, in the medical information storage module, personalised configuration is set, in the medical information accurate recommendation module, the user interest model is quantified by vector space method, and BP algorithm and SOM algorithm are introduced to complete the accuracy of medical information recommend. The experimental results show that: the highest accuracy rate of medical information recommendation is 98.8%, and the shortest retrieval response time is 20 ms.
    Keywords: big data technology; medical information; preprocessing; accurate recommendation.
    DOI: 10.1504/IJISE.2020.10035264
  • Design Of Energy Consumption Monitoring System Of Public Buildings Based On Artificial Neural Network   Order a copy of this article
    by Hui-hua Xiong, Chuan He, Jin Lin, Xin Xiang, LiE Yu 
    Abstract: In order to overcome the problems of low monitoring accuracy and long response time in traditional energy consumption monitoring system of public buildings, a new energy consumption monitoring system of public buildings based on artificial neural network is proposed. The system hardware is designed by using the energy consumption collection subsystem and energy consumption data transmission subsystem of public buildings. Through the genetic algorithm to optimise the constraint parameters of the physical sign extraction function to obtain the characteristics of public building energy consumption, combined with the main factors affecting the building energy consumption, the public building energy consumption monitoring model based on artificial neural network is established, and the real-time monitoring of public building energy consumption is realised through the model. The experimental results show that, compared with the traditional monitoring system, the minimum monitoring error of the designed system is only 0.01.
    Keywords: artificial neural network; public building; energy consumption monitoring system; genetic algorithm.
    DOI: 10.1504/IJISE.2020.10035319
  • Research On Energy Consumption Control Method Of Green Building Based On Bim Technology   Order a copy of this article
    by Jianhong Xu 
    Abstract: In order to overcome the problems of large energy consumption control error and low control efficiency in traditional energy consumption control methods, a new energy consumption control method based on BIM technology is proposed in this paper. In this method, RSstudio data mining software is used to mine the energy consumption data of green buildings in CBECS building energy consumption information database to fill the data shortage. Using the orthogonal test method and building information simulation software to analyse the significance level of energy consumption of green building, simulate the energy consumption of green building, based on BIM technology, implement the integrated design of energy consumption control of green building, in order to achieve the energy consumption control of green building. The experimental results show that the proposed energy consumption control method has lower control error and higher control efficiency, and the maximum control error is only 0.44.
    Keywords: BIM technology; green building; energy consumption control; energy consumption simulation.
    DOI: 10.1504/IJISE.2020.10035323
  • Solar panel selection using an integrated analytical hierarchy process and multi-objective optimization by ratio analysis: an empirical study   Order a copy of this article
    by Gnanasekaran Sasikumar, A. SIVASANGARI 
    Abstract: A solar panel is a vital element of a photovoltaic (PV) system. Hence, it is essential to study the reduction of material costs of a solar panel without compromising the efficiency of it. Selection of solar panel is a complex problem due to the presence of various quantitative and qualitative parameters. This paper deals with the development of a mathematical model by combining analytical hierarchy process (AHP) and multi-objective optimisation by ratio analysis (MOORA) for the evaluation and ranking of solar panels. The AHP method is utilised to fix compromise solution with incommensurable and contradictory criteria, consisting of five potential solar panels and eight selection parameters. The AHP technique is adopted for calculating the criteria weights based on the relative importance. Consequently, MOORA method is used for ranking and selecting the solar panel alternatives. The proposed AHP and MOORA approach is found to be effective for the evaluation and ranking of solar panels as it produces comparable results with VIKOR method. In the VIKOR method, alternatives are ranked based on closeness to positive ideal solution.
    Keywords: solar panel; analytical hierarchy process; AHP; multi-objective optimisation; multi-criteria decision-making; MCDM; ratio analysis; VIKOR.
    DOI: 10.1504/IJISE.2020.10035476
  • Research on the early warning system of regional financial risk   Order a copy of this article
    by Xiaowei Lin, Yaqin Peng 
    Abstract: It is a systematic research work to design the early warning system of regional financial risk. This paper selects a total of 17 regional financial risk early warning indicators from the aspects of external macro-impact, regional macro-economic and regional micro-finance, and then uses the mapping method, GRITIC method and comprehensive scoring method to deal with the index standardisation, index weight and comprehensive risk measurement respectively, and construct the regional financial risk early warning system. Based on the empirical research of Fujian Province’s actual data, the results show that there are implied fluctuations in the overall stability of regional finance in Fujian Province from 2013 to 2017, but some important early warning indicators still have different levels of risk. Finally, according to the early warning results of Fujian Province, the targeted financial risk prevention measures are put forward.
    Keywords: regional financial risk; early warning system; mapping treatment; GRITIC method.
    DOI: 10.1504/IJISE.2020.10035477
  • The efficient routing approach of a vehicle under the vehicle routing problem with simultaneous delivery and pickup for reducing the fuel consumption and pollutants emission   Order a copy of this article
    by Nilufa Yeasmin, Sultana Parveen 
    Abstract: The vehicle routing problem with simultaneous delivery and pickup (VRPSDP) has received significant attention in logistics operations to minimize the travelling distance or travelling time. However, little is known regarding the VRPSDP in logistics operations which is used to reduce the emission of CO2 in the environment (i.e., critical requirements of green logistics). Our study proposes the fuel-optimization model for the vehicle under VRPSDP referred to as an eco-friendly VRPSDP model. This model aims to determine the efficient vehicle route that will reduce the vehicle's fuel consumption as well as decrease the negative impact on the environment. The Genetic Algorithm (GA) is applied to solve the proposed fuel optimization model. Here, two types of genetic mutation operator, i.e. swap and inverse are used to find out which one would give the optimum results regarding fuel consumption. The computational tests show that that the inverse mutation performs better than the swap mutation and saves the fuel consumption of 4.1 % over the swap mutation.
    Keywords: fuel optimisation; vehicle routing problem with simultaneous delivery and pick up; genetic algorithm; swap mutation and inverse mutation; reverse logistics.
    DOI: 10.1504/IJISE.2020.10035591
  • Patient Safety Culture in Al Zarqa Public Hospital: Case Study   Order a copy of this article
    by Osama Al-meanzel, Haetham Doweire, Hesham A. Almomani 
    Abstract: Patient safety concerns vary among healthcare provider settings, cultures of countries, policies and available resources. The primary purpose of this study is to analyse and establish a baseline assessment of the patient safety culture in Al Zarqa governorate hospitals. Hospitalised patients need to receive appropriate and high-quality treatment recommended in accordance with the latest professional knowledge. This study was conducted at two hospitals in Al Zarqa City, Prince Faisal Hospital (Prince Faisal Bin Al-Hussein Hospital) and Al Zarqa New Hospital (Al Zarqa Governmental Hospital). The total number of the participant was 131 from hospitals from 14 departments (59% from Al Zarqa New Hospital and 41% from Prince Faisal Hospital). The results of this study suggest that patient safety culture in Al Zarqa public hospitals needs more attention. The majority of the participant neither agreed nor disagreed on most of the points survey. However, they reported certain events that compromised safety, and at times having communicated with the hospitals about safety issues. Patient safety issues vary according to the setting, local culture, and available resources.
    Keywords: patient safety culture; PSC; human safety; quality; healthcare; safety; patient culture.
    DOI: 10.1504/IJISE.2020.10035862
  • An innovative forestry chassis with legs Installed bionic walking foot   Order a copy of this article
    by Tingting Sui, Jinhao Liu, Liang Chen, Qingqing Huang, Tiebo Sun 
    Abstract: This paper studies a creative forestry chassis installed bionic walking foot with adjustable support foot (FC-BWF&ASF) based on bionic principle, proposes a method to improve terrain trafficability by avoiding direct contact with obstacles and pits of unpredictable shapes and dimensions in forestland, which is realised by controlling the posture of BWF&ASF. The kinematics model is established by D-H method and trajectory is planned with compound cycloid method. Finally, the effectiveness is verified through simulation experiment in ADAMS. The results show that the chassis can surmount obstacle of 60 mm height as ASF rotates 45 degrees, while no rotation is needed to move over sunken pit of 120 mm width. Additionally, the fluctuation range of frame barycentre in two conditions is within 1 mm and 4 mm, respectively. The conclusion shows that within structural parameters, the novel foot structure contributes to cross irregular terrain with quiet good stability.
    Keywords: forest chassis; mechanical model; kinematics analysis; passing strategy; multibody dynamics simulation.
    DOI: 10.1504/IJISE.2020.10036042
  • Exchange rate risk sharing model of transnational supply chain considering background risk   Order a copy of this article
    by Zhe Wang, Yanyu Chen, Chunjiao Gao 
    Abstract: By extending the single exchange rate risk in previous studies to a general additive and multiplicative background risk form, this paper proposes a game model including a retailer, a manufacturer and a supplier. Explicit expressions of the optimal decisions for the retailer, the manufacturer and the supplier are given, respectively. Furthermore, the impacts of different forms of risk on the risk-sharing behaviour of the node enterprises in the supply chain are discussed. It is found that, if there is only additive background risk, there is no risk-sharing behaviour between the retailer and the manufacturer. When multiplicative background risk exists, both retailers and manufacturers share the background risk and price risk. The risk sharing degree between retailers and manufacturers increases with the fluctuation of background risk factors, and the risk sharing degree between suppliers (retailers) and manufacturer decreases with the increase of price risk.
    Keywords: supply chain decision; additive background risk; multiplicative background risk; risk-sharing.
    DOI: 10.1504/IJISE.2020.10036248
  • Industry 4.0: Prospectives and Challenges leading to Smart Manufacturing   Order a copy of this article
    by Ramesh Rudrapati 
    Abstract: Fourth Industrial Revolution proposed advancements in production processes and its automation. Industry 4.0 (I4.0) is a broad domain to create smart factory which includes manufacturing methods, economy, data management, relationships between consumer and manufacturer, etc. I4.0 is new themes of research to produce smart products which need to be explored at bottom levels of prospects and goals by academicians, business scholars, various contributors of scientific community. Main aim of the present study is to review the prospects and challenges of I4.0 related various issues and aspects of smart manufacturing. Important components in I4.0 are also explored and discussed. Status of research works on I4.0 and its applications are included. Challenges faced by industrialists are mentioned and discussed. Various features and issues related to I4.0 discussed in the present study will expected to clarify the aims and fundamental components of I4.0. Concluding remarks has been drawn from the study.
    Keywords: Industry 4.0; smart manufacturing; prospects of I4.0; challenges of I4.0.
    DOI: 10.1504/IJISE.2021.10036284
  • Design Of The Autonomous Learning System For Students In Remote Open Education Based On Mooc   Order a copy of this article
    by Yingwei Geng 
    Abstract: In order to realise the new education mode of students’ autonomous learning and meet the learning needs of open education, this paper proposes the design of students’ autonomous learning system based on MOOC. First of all, the embedded scheduling method is used to sample the students’ information, the distance open education independent learning resources are used, and the sampling information and statistical average analysis method are used to control the students’ autonomous learning mode in moo. Through the adaptive optimisation of machine learning, the autonomous learning system of students in distance open education is optimised and simulated. The result shows that this method has a good adaptive ability in distance open education, and effectively enhances the autonomous learning ability of distance education students.
    Keywords: mass open online course; MOOC; remote open education; autonomous learning; system design.
    DOI: 10.1504/IJISE.2020.10036291
  • Computer aided ergonomics design and comparative analysis of waiting chairs at a health centre   Order a copy of this article
    by Feyisayo Akinwande, Olusegun Akanbi, Samson Akindele 
    Abstract: This study explains the ergonomics design and comparative analysis of chairs (waiting) at a health centre using anthropometric data and CATIA V5R20 software to perform finite element analysis (FEA) and determine the most efficient ergonomic design. From the collected data, the analysis was conducted based on percentiles; with the use of Excel. The modelling of the chairs was performed using its materials. FEA was also conducted for the designed waiting chairs to check, for stress, deformation and displacement. The human builder part of CATIA V5R20 was used to test, for the efficiency and the physical interaction across the user and the designed chair. The results obtained showed that computer-aided ergonomics design is not limited to anthropometric data collection, and designing of products. It is also a means of determining the quality of the designed product.
    Keywords: ergonomics design; computer-aided design; CATIA V5R20; FEA analysis; anthropometrics; chairs.
    DOI: 10.1504/IJISE.2021.10036538
  • Design of cloud service system for enterprise economic management based on hybrid cloud mode   Order a copy of this article
    by Mi Wang 
    Abstract: In order to overcome the problems of traditional enterprise economic management cloud service system, such as long response time, this paper designs a cloud service system for enterprise economic management based on hybrid cloud mode. The system hardware is composed of server, optical switch, optical disk storage cabinet and management module. On the basis of the hardware design, the system software is designed. The K-means algorithm is used to mine the enterprise economic data, and the data is standardised and stored in the database. The experimental results show that the system designed in this paper has good compatibility and concurrency performance, and the system response time is always less than 0.5 s, and the user satisfaction is between 6.8 to 9.6, so the practical application effect is better.
    Keywords: hybrid cloud model; enterprise; economic management; cloud service system; information retrieval.
    DOI: 10.1504/IJISE.2020.10036703
  • k-Most Suitable Locations Problem: Greedy Search Approach   Order a copy of this article
    by Seyed-Hadi Mirghaderi, Behnam Hasanizadeh 
    Abstract: Facility location problems have been highly considered in the literature and employed in various real-world situations. The k-most suitable locations (k-MSLs) is a type of site-selection problem, a direction of facility location problems. It can be applied in several areas like disaster management, urban development, telecommunication and franchising corporations. This paper aims to develop heuristics for the problem. It proposes four greedy search algorithms to find solutions for the k-MSL problem and provide a baseline for comparing future solutions. The proposed greedy algorithms solve the problem for all values of k. The computational experiments using real-world datasets reveal that one of the developed algorithms is superior in consuming CPU time, and the other three algorithms provide accurate solutions in low k and good solutions in all values of k in a reasonable time.
    Keywords: location science; k-most suitable locations; k-MSLs; heuristics; facility location; greedy search.
    DOI: 10.1504/IJISE.2021.10036732
  • Solving multi-objective flexible flow-shop scheduling problem using teaching-learning-based optimization embedded with maximum deviation theory   Order a copy of this article
    by Raviteja Buddala, Siba Sankar Mahapatra, Manas Ranjan Singh 
    Abstract: Flexible flow-shop scheduling problem (FFSP) is an extended special case of basic flow-shop scheduling problem (FSP). FFSP is treated as complex NP-hard scheduling problem. A good scheduling practice enables the manufacturer to compete effectively in the market place. An efficient schedule should address multiple conflicting objectives so that customer satisfaction can be improved. In this work, a novel approach based on teaching-learning-based optimisation (TLBO) technique incorporated with maximum deviation theory (MDT) is applied to generate schedules that simultaneously optimise conflicting objective measures like makespan and flowtime. Results indicate that the proposed multi-objective TLBO (MOTLBO) outperforms non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimisation (MOPSO) in majority of the problem instances.
    Keywords: flexible flow-shop scheduling; FFSP; flowtime; makespan; maximum deviation theory; MDT; non-dominated solutions; multi-objective optimisation; teaching-learning-based optimisation; TLBO.
    DOI: 10.1504/IJISE.2021.10037222
  • Modelling of Critical Success Factors for Blockchain Technology Adoption Readiness in the Context of Agri-Food Supply Chain   Order a copy of this article
    by Vipulesh Shardeo, Anchal Patil, Ashish Dwivedi, Jitendra Madaan 
    Abstract: The agri-food supply chain is continuously facing several challenges; the most severe are food quality and safety issues. These issues debilitate the performance of the supply chain and often harm the consumers health. Therefore, there is an urgent need to address food quality and safety assurance in the supply chain. Blockchain technology (BCT) holds the potential to resolve these issues by enhancing security and transparency. The present study explores the critical success factors (CSFs) of BCT adoption readiness in the AFSC. Initially, CSFs are identified through a literature survey and finalised by experts opinion. The finalised factors are prioritised using the fuzzy best-worst method, followed by sensitivity analysis. The results reflect that food quality control, provenance tracking and traceability, and partnership and trust as the top three success factors. The studys findings will assist policymakers, managers, and practitioners in strategising the decision-making process while BCT dissemination.
    Keywords: blockchain technology; agri-food supply chain; AFSC; fuzzy; best-worst method; BWM; trust.
    DOI: 10.1504/IJISE.2021.10037223
  • Analytical Solution and Optimization of serial supply chains with multiple nodes, lost sales, continuous review replenishment policies, stochastic lead times and external demand   Order a copy of this article
    by Michail Geranios, Michail Vidalis, Stylianos Koukoumialos, Alexandros Diamantidis 
    Abstract: This work analyses a serial supply chain with an arbitrary number of nodes (retailer, wholesaler, manufacturer, supplier, etc.). Every node faces supply uncertainty in both replenishment lead time and quantity delivered (except for the most upstream node, assumed saturated). The most downstream node (retailer) faces external Poisson demand with rate . Each node follows a continuous review (si, Si), i = 1, 2, , K 1 replenishment policy. If a node is insufficiently stocked, then the order is only partially satisfied. The system parameters that influence the performance of the supply chain are the number of nodes, the upper level of inventories, the reorder levels, the replenishment times, and the demand rate. The supply network is modelled as a continuous time Markov process with discrete states. We explore the structure of the transition matrices and develop a computational algorithm to generate the stationary probability distributions for any combination of the system parameters. We also use the proposed algorithm as a design and optimisation tool to determine the optimal inventory policies (i.e., reorder level and order-up-to-level) to maximise the fill rate (FR) or minimise the work-in-process (WIP) for multi-echelon serial supply chains.
    Keywords: supply chain management; SCM; inventory control; lost demand; continuous review policy; performance evaluation.
    DOI: 10.1504/IJISE.2020.10037226
  • Simulation-based Optimization: Analysis of the Emergency Department Resources under COVID-19 Conditions   Order a copy of this article
    by Shahla Jahangiri, Milad Abolghasemian, Peiman Ghasemi, Adel Pourghader Chobar 
    Abstract: The emergency department (ED) is the most important section in every hospital. The ED behaviour is adequately complex, because the ED has several uncertain parameters such as the waiting time of patients or arrival time of patients. To deal with ED complexities, this paper presents a simulation-based optimisation-based meta-model (S-BO-BM-M) to minimise total waiting time of the arriving patients in an emergency department under COVID-19 conditions. A full-factorial design used meta-modelling approach to identify scenarios of systems to estimate an integer nonlinear programming model for the patient waiting time minimisation under COVID-19 conditions. Findings showed that the S-BO-BM-M obtains the new key resources configuration. Simulation-based optimisation meta-modelling approach in this paper is an invaluable contribution to the ED and medical managers for the redesign and evaluates of current situation ED system to reduce waiting time of patients and improve resource distribution in the ED under COVID-19 conditions to improve efficiency.
    Keywords: emergency department; simulation-based optimisation; S-BO; meta-model; COVID-19.
    DOI: 10.1504/IJISE.2021.10037641
  • Assessment of Suppliers and Optimum Order Allocation in Agile Automotive Manufacturing Companies   Order a copy of this article
    by Masoud Rahiminezhad Galankashi, Aida Rezaei, Mobina Keyvanpazhooh, Farimah Mokhatab Rafiei 
    Abstract: This paper develops a systematic approach to assist agile automotive manufacturers to assess their potential suppliers and allocate required orders. Agile manufacturing (AM) and its related concepts have been discussed in previous literature. However, its integration with purchasing and supplier selection is less examined. Therefore, the development process of agile supplier selection framework is the main addressed problem of this research. A comprehensive investigation on previous studies and analytic hierarchy process (AHP) were applied to finalise agile supplier selection criteria. Next, the developed agile supplier selection criteria were applied to assess suppliers using fuzzy analytic hierarchy process (FAHP). Finally, a multi-period and multi-objective order allocation model was developed to determine optimum agile purchasing quantity of items from suppliers. Therefore, the main outputs of this research include agile supplier selection criteria, ranking of suppliers and multi-period purchasing quantity from suppliers. In addition, a sensitivity analysis was applied to provide more understandable and practical outputs.
    Keywords: supplier selection; agile manufacturing; AM; order allocation; analytic hierarchy process; AHP; fuzzy analytic hierarchy process; FAHP.
    DOI: 10.1504/IJISE.2021.10037642
  • Optimization study on the drain mode of cycloidal rotor oil pump   Order a copy of this article
    by Wen Wang, Xiang Liu, Hao Cai, Shanghong He, Yuelin Li 
    Abstract: In order to optimise the internal flow field pulsation characteristics of a cycloidal rotor oil pump, the internal oil drain structure of the pressure limiting valve was changed to an external oil drain structure. The numerical simulation method is used to calculate the internal flow field of the cycloidal oil pump with different drain structures. The outlet pressure pulsation, pressure pulsation at the pressure limiting valve, displacement of the pressure limiting valve spool and cavitation are compared and analysed. The results show that, relative to internal drain structure, the pressure amplitude of the external drain structure at the pressure limiting valve is reduced by 30%, the pressure amplitude at the outlet is reduced by 25%, and the cavitation phenomenon at the interface between the pressure limiting valve and the inlet cavity is eliminated. The bench test is carried out to verify the sample pump, and the test results are in good agreement with the simulation results, with the volume efficiency improved by up to 4%.
    Keywords: cycloidal rotor oil pump; pressure pulsation; pressure limiting valve; oil drain structure.
    DOI: 10.1504/IJISE.2021.10037885
  • Supply Chain Network Design under Distribution Center Disruption   Order a copy of this article
    by Huynh Trung Luong, Ashish Devkota, Sidharath Joshi 
    Abstract: In the 21st century, with the rise of increasing competition and highly volatile customer demands, managing and designing supply chain networks have become critical in most industries. While designing the supply chain, disruption must be taken into consideration. However, when dealing with supply chain disruptions, most of past research works focused only on uncertainties/disruptions at supply side or demand side. In fact, disruptions should also be considered at distribution centres. This research aims at deriving a mathematical model for a three-stage logistics network consisting of a single manufacturing plant, multiple potential locations for opening distribution centres with associated risk of disruption, and multiple customer zones. A scenario-based mathematical modelling approach is used to determine the locations at which a fixed number of distribution centres should be opened. The key challenge in developing the combined total cost function which incorporated all disruption scenarios is how to develop a general expression for the probabilities of occurrence of various disruption scenarios. This is the unique contribution of this research in terms of mathematical model development. Numerical experiments were then performed to illustrate the applicability of the proposed model. Sensitivity analyses have also been conducted to examine the robustness of the solution.
    Keywords: supply chain network design; SCND; location-allocation problem; mixed integer linear programming; disruption; risk; uncertainty.
    DOI: 10.1504/IJISE.2020.10037908
  • Analyzing the Supply Chain Network Reconfiguration under Disruption Risk Environment   Order a copy of this article
    by Varthini Rajagopal, S. Prasanna Venkatesan, Usha Mohan, Rishabh Gaur, Shubham Jha 
    Abstract: A p-robust supply chain network (SCN) reconfiguration model under disruptions in dynamic mid-term horizon considering decision-maker (DM)’s risk-attitude is presented. Reconfiguration of SCN within a time horizon by utilising excess resources of undisrupted facilities, outsourcing and capacity expansion is studied. At first, the single-objective cost minimisation problem is formulated and extended as a multi-objective problem incorporating responsiveness as another objective. Pareto solutions are obtained using augmented ?-constraint (AUGMECON) method. The major inferences include: 1) the cost minimisation model opens a fewer facility under nominal condition and prefers capacity expansion strategy under disruptions. The inclusion of responsiveness objective results in opening more facilities with outsourcing as preferred reactive strategy; 2) DM’s attitude significantly affect structural decisions but not the parametric decisions such as capacity expansion, material flow redirection, and outsourcing; 3) a neutral DM selects a dispersed and diversified portfolio of facilities; whereas averse DM opens backup facilities closer to critical facilities.
    Keywords: dynamic configuration; disruption; reactive mitigation strategies; risk-attitude; responsiveness; AUGMECON.
    DOI: 10.1504/IJISE.2020.10037923
  • Personalized resource recommendation method for collaborative tagging system based on machine learning   Order a copy of this article
    by Xiaofei Liu 
    Abstract: In order to overcome the low feasibility of traditional resource recommendation methods, this paper proposes a personalised resource recommendation method based on machine learning. Firstly, the user-based collaborative filtering algorithm is used to calculate user personalised similarity, and then content-based collaborative filtering algorithm is used to calculate resource content similarity through cosine similarity. Combined with user similarity and resource content similarity, a hybrid computing model of resource similarity is established, and personalised recommendation is realised through statistical machine learning. The experimental results show that: the F-measure value of the method can reach 0.97, the coverage rate is maintained above 50%, the popularity is above 0.8, and the MAE value is always the minimum, and its precision is always higher than that of the contrast method. It shows that the proposed method can effectively improve the precision and feasibility of personalised recommendation results.
    Keywords: machine learning; collaborative tagging system; personalised resource recommendation; similarity.
    DOI: 10.1504/IJISE.2020.10037928
  • Innovative Local Search Heuristics for Uncapacitated Facility Location Problem   Order a copy of this article
    by Shahed Sholekar, Mehdi Seifbarghy, Davar Pishva 
    Abstract: This paper presents four different local search heuristics, abbreviated as PSC, PSTC, PTSC and PFSC, for handling the UFLP. It compares their outcome with that of a previously proposed equivalent heuristic called add-swap neighbourhood search (ASNS). One of its main focus is to reduce processing time since ASNS heuristics computational time is quite long and continues to increase in an exponential order with magnitude of the problem. The proposed heuristics use a two-phase approach wherein the first phase ranks the potential facilities locations and selects an initial solution from the ranking; and the second phase keeps on adding other locations from the ranking list, one at a time, until the stop criterion is achieved. Its results show that the proposed heuristics reduce computational time dramatically when compared with the ASNS. Furthermore, the PFSC heuristic provides better performance in both computational time and solution quality when dealing with large size problems.
    Keywords: location; UFLP; uncapacitated; local search; heuristics; mixed-integer programming.
    DOI: 10.1504/IJISE.2021.10038029
    by Yuval Cohen, Maurizio Faccio, Mauro Gamberi 
    Abstract: Assembly lines are characterised by high rates of turnover and absenteeism. Any case of absenteeism or turnover requires assigning a replacement worker who is often inexperienced. Learning process is crucial for increasing productivity in such replacement cases, but learning is dependent on the variety of product models produced on that line. The complexity effect of the tasks at the assembly station, owing to a multi-model pattern, can result in a forgetting curve. The current research investigates the absenteeism in various batch sizes of multi-model and mixed-model assembly lines, introducing an innovative adaptation of the learning and forgetting functions. Secondly, it analyses the assembly system performance through a simulation study, focusing on the models’ commonality and models sequences in the case of new substitute workers. A case study and a simulation analysis are reported to validate the research.
    Keywords: absenteeism; turnover; learning; forgetting; multi-model; mixed-model.
    DOI: 10.1504/IJISE.2021.10038031
  • Application of Machine Learning Techniques in Chronic Disease Literature: from Citation Mapping to Research Front   Order a copy of this article
    by Md. Abul Kalam Azad, Rakibul Hoque, Jinnatul Raihan Mumu, Peter F. Wanke 
    Abstract: This study aims to conduct a hybrid review on applying machine learning techniques in chronic disease literature using both bibliometric and systematic review techniques. The dataset consists of 206 Scopus indexed journal articles from 2004 to 2020. The bibliometric results identify the most contributing authors, journal sources, author network, bibliometric coupling of documents, and the co-citation network. The systematic review reveals the most promising research areas, which include machine learning algorithms integrated with other techniques such as deep learning, artificial neural network, and data mining to predict chronic diseases in gastroenterology, cardiology, and neurology. Although machine learning techniques are rising in popularity in chronic disease literature, there is more room for improvement such as the challenges involved in using machine learning to predict chronic diseases, feasibility studies, and the necessity of rehabilitation and readmission in hospitals to predict a chronic attack.
    Keywords: machine learning; chronic disease; diabetes; deep learning; bibliometric analysis; systematic review.
    DOI: 10.1504/IJISE.2021.10038298
  • Design of a machine learning to classify health beverages preferences for elderly people: an empirical study during COVID-19 in Thailand   Order a copy of this article
    by Athakorn Kengpol, Jakkarin Klunngien 
    Abstract: This research designed a decision support system based upon a machine learning (DSS-ML) model for classifying health beverage preferences for elderly people. A neural network was designed involving training using particle swarm optimisation (PSO) in comparison with two ML models: logistic regression (LR) and a neural network (NN). The DSS-ML model was able to classify accurately and autonomously the preference complexities associated with the health beverage preferences for elderly people in accordance with the WHO’s recommendation. In terms of contribution, the results demonstrated that NN training with PSO resulted in a higher ability to classify the preferences for health beverages than for the two ML models. Furthermore, NN training with PSO achieved faster convergence than NN. The benefits of this research can be separated into two parts. First, manufacturers can introduce beverages that satisfy elderly people’s preferences. Second, elderly people can be made aware of appropriate health beverages.
    Keywords: decision support system; DSS; machine learning; elderly people; neural network; particle swarm optimisation; PSO; logistic regression.
    DOI: 10.1504/IJISE.2021.10038478
  • Lot Streaming of Hybrid Flowshops with Variable Lot Sizes and Eligible Machines   Order a copy of this article
    by Enas Ahmed Zaky, Tamer F. Abdelmaguid, Tamer Adel Mohamed, Sayed Taha Mohamed 
    Abstract: Hybrid flowshops are a special type of manufacturing systems, in which a stage may contain identical or unrelated parallel machines. This paper deals with a more practical approach for lot streaming hybrid flowshop in which the sublot sizes of jobs can vary from one stage to the next according to machines `speed. Two models of mixed-integer nonlinear programming are developed to minimise the make-span of two different hybrid flowshop systems. The first model deals with unrelated parallel machines with eligibility, independent setup time, and variable sublot sizes. The second model is a special case of the hybrid flowshop as it consists of multi-stages comprising one machine at the stages preceding the final stage, while the final stage includes unrelated parallel machines. The first model was studied and the data gathered were analyzed using ANOVA test to evaluate the factors’ effect on system. The factors are number of jobs, maximum number of batches, setup time, and machine’s configuration. The analysis revealed that all the factors were effective. The second model was compared to benchmarking published paper and it gets better results.
    Keywords: hybrid flowshop; HFS; sublots; make-span; mixed-integer nonlinear programming; eligible machines.
    DOI: 10.1504/IJISE.2021.10038498
  • Application of Systems Engineering to design the architecture of an enterprise of wind turbines inspection   Order a copy of this article
    by Marcelo Sousa, Renan Barros, João Pedro Simas, Rogério Coimbra 
    Abstract: The use of systems engineering techniques is presented in this work to design the architecture of an enterprise of wind turbines inspection. The motivation for this research is the possibility to acquire detailed data in order to make one improved technical and financial feasibility analysis. This way, it is considered that there will be lower risks and higher return of investment. The use of systems engineering included the problem definition, requirements specification, requirements validation, and definition of physical and logical architecture descriptions. All this information offered more data to perform more detailed calculus of investment needed to create this enterprise, and the price of the offered service.
    Keywords: systems engineering; enterprise architecture; wind turbines inspection; renewable energy; enterprise systems engineering; ESE.
    DOI: 10.1504/IJISE.2021.10038561
  • The energy consumption in the turbocharger manufacturing system   Order a copy of this article
    by Jean G. Azarias, Aparecido R. Coutinho 
    Abstract: The quantification of energy consumption in manufacturing systems is an essential step for the formulation of energy efficiency strategies. In the transport sector, turbochargers are important devices, which the manufacturing system shows intense energy consumption. This study aims to quantify energy consumption throughout the manufacturing system of a turbocharger. A case study was conducted to analyse the data collected in a turbocharger manufacturer. The total energy consumption is 347.15 MJ, with 240.28 MJ corresponding to the energy consumption for component production. This is the first experimental work related to the turbocharger production, in which the main technical contribution is focused on the LCA throughout various stages of the production process. In addition, the information presented can be used to conduct a comparison with other manufacturing systems and contribute to the development of greater energy efficiency in the automotive industry.
    Keywords: energy consumption; turbocharger; life cycle energy assessment; LCEA; manufacturing; life cycle assessment; LCA.
    DOI: 10.1504/IJISE.2021.10038569
    by Mohsen Fayyazi, Siamak Haji Yakhchali, Mir Saman Pishvaee, Fariborz Jolai 
    Abstract: Because of high volatility in oil price, oil companies should change their strategies along with changing oil prices. Thus, dynamic portfolio management is strongly recommended to increase the rate of oil production and determine resource allocation for projects in each period of the planning horizon. To achieving the aim, a two-stage stochastic mathematical model is developed to optimise the portfolio of oil projects. To make the model more realistic, splitting the projects and their resumption are permitted. To solve the model, a robust optimisation approach is designed, and the results of the robust and two-stage stochastic designs are compared. These comparisons are based on a realisation algorithm developed by this study. To illustrate the capability and power of the stochastic model in handling the uncertainty, a case study on an oil company is presented.
    Keywords: portfolio management; resource assignment; project scheduling; stochastic programming; robust optimisation.
    DOI: 10.1504/IJISE.2021.10038570
  • Analytic Hierarchy Process as a decision-making tool for Systematic Layout Planning, involving social responsibility criteria: a case study   Order a copy of this article
    by Lucas Schmidt Goecks, Taciana Mareth, Andre Luis Korzenowsk, Jorge Moraes, Elpídio Nara 
    Abstract: Layout planning is a significant business problem for companies, it involves reducing inventories, lead time and space usage, making the plant adaptable to future changes, and providing a healthy, convenient, and secure environment for employees. In convergence with these goals, decision-making becomes a vital activity to reach a reasonable choice. In this way, this study aimed to analyse the contribution of the analytic hierarchy process (AHP) to systematic layout planning (SLP) as a method of layout planning for company managers, involving social responsibility criteria. Firstly, a technical study was performed presenting possibilities of layouts from the tools for SLP planning. Next, the best proposal was selected using the AHP. The results show that layouts 4 and 2 are the ones that best meet the needs of the company under analysis. Already, layouts 5 and 1, because they have a very long flow of materials, have shown inferior results.
    Keywords: systematic layout planning; SLP; analytic hierarchy process; AHP; layout planning; social responsibility criteria.
    DOI: 10.1504/IJISE.2020.10038574
  • A Model-Based Decision Framework for the Multi-Depot Multi-Traveling Salesman Problem with Split and Delivery Demand considering different Key Performance Indicators   Order a copy of this article
    by Daniela Contreras, Rodrigo Linfati, John Wilmer Escobar 
    Abstract: This paper introduces the multi-depot multi-travelling salesman problem with split and delivery demand (MmTSP-SD). The problem has been formulated as a flexible optimisation model that considers four key performance indicators (KPIs): the minimisation of the route distance, the minimum daily demand to satisfy, similar demand between crews, and the equivalent kilometres travelled between crews. The efficiency of the proposed approach has been tested in three types of instances adapted from a green area maintenance company dedicated to the management of any vegetation, cutting grass or weeds and/or collecting leaves, watering, or fertilising, among many other services. The results confirm the efficiency of the proposed approach and the positive impact in determining the different performance measures that are considered.
    Keywords: multi-travelling salesman problem; m-TSP; balance of travellers; key performance indicator; KPI; MmTSP-SD; visit planning; mixed-integer linear programming.
    DOI: 10.1504/IJISE.2021.10038690
  • Goal programming approach for agile sustainable pharmaceutical supply chain   Order a copy of this article
    by Meghdad Haji Mohamad Ali Jahromi, Ali Nazeri, Ehsan Ghorbani 
    Abstract: In this paper, a pharmaceutical supply chain network with four levels including suppliers, major distributors, retailers and customers was considered and in order to have agility and sustainability benefits simultaneously, goal programming approach has been used. In fact, an optimum structure regarding sustainable aspects of supply chain in light of economic, social, environmental and political aspects (i.e., as important aspects in the current situation) were designed. Also, for this purpose, a digraph corresponded to a feasible structure under real situation of pharmaceutical supply chain was considered, and then with help of goal programming approach, an optimum configuration, which is a sub-digraph from the main, will be achieved. Results show that the model has high capability to configure pharmaceutical chain according to expectations of the managers and experts of the chain.
    Keywords: sustainable supply chain; goal programming; pharmaceutical supply chain.
    DOI: 10.1504/IJISE.2021.10038796
  • PMP approach for solving the binary static multi-objective generalized cell formation problem   Order a copy of this article
    by Youkyung Won 
    Abstract: The p-median problem (PMP) approach has been used as an effective alternative for solving small-to-medium-sized single-objective cell formation (SOCF) problems. Cell load balancing is an important consideration in multi-objective cell formation (MOCF) problems for reflecting realistic manufacturing factors. However, few cell formation (CF) studies using the conventional PMP approach with the binary machine-part incidence matrix (MPIM) alone have considered multiple objectives including cell load balancing because the conventional binary MPIM can only indicate whether parts are processed on particular machines. In this study, we emphasise the importance of cell load balancing even in binary MPIM-based multi-objective generalised cell formation (MOGCF) problems with alternative process plans for parts and demonstrate that the binary MPIM-based CF without consideration of cell load balancing can lead to inferior solutions. This study shows that the PMP approach can effectively solve large-sized MOGCF problems by considering the minimisation of cell load imbalance and inter-cellular part moves, which result in inefficient cells. Our PMP approach first solves the SOCF problem and then attempts to satisfy conflicting multiple objectives ex post facto with a subsequent heuristic procedure. The computational results show that the proposed PMP approach is very effective for large-sized MOGCF problems.
    Keywords: PMP approach; generalised multi-objective cell formation; cell load balancing.
    DOI: 10.1504/IJISE.2021.10038798
  • Selection of Engine Oil Using Multi Attribute Decision Making Methods.   Order a copy of this article
    by Akash Salunke, Rupesh Satpute, Akash Neharkar, Avinash Kamble, Ajit Lokhande 
    Abstract: The role of internal combustion engines in automobile industry has already been well recognised. It is made with closer precisions thus involve higher costs and also, it is crucial to ensure efficient working of its various components. Engine oil of specific grades is used for reducing wear and tear of components and cooling of parts of the engine. Choice of appropriate engine oil for engines is critical task for designers. Designers need to identify oils with specific properties and functionalities in order to fulfil end requirements and desired functionalities of the engine. The different oils possess different properties. Systematic approach must be used for selection of oil. Thus, the present work focuses on the selection procedure for best engine oil using four selected multi attribute decision making. The proposed methods help to evaluate and rank different engine oils in order to assist the decision maker in selecting appropriate engine oil.
    Keywords: multi-attribute decision-making methods; engine oils selection; preference ranking organisation method for enrichment evaluation; additive ratio assessment method; organisation rangement et synthese de donnes relationnelles method; elimination and choice translating reality method; analytical hierarchy process.
    DOI: 10.1504/IJISE.2021.10038998
  • Research On Optimization Method For Project Site Selection Based On Improved Genetic Algorithm   Order a copy of this article
    by Ling-min Yang, Zhong-min Tang, Sijun Liu 
    Abstract: In order to overcome the problems of low correlation between location impact index and target project, and low customer satisfaction in current research methods of project location, an optimisation method of project location based on improved genetic algorithm is proposed and designed. Collect the data needed for project site selection and integrate relevant data efficiently, and build the framework structure of project site selection. According to the evaluation index of project location, the existing genetic algorithm is improved. The improved genetic algorithm is applied to the optimisation of project location, and the eigenvalues and correlation factors of project location are optimised to realise the optimisation of project location. The experimental results show that the fit degree between the proposed method and the target project is between 0.9 to 1.0, and the user satisfaction is between 95 % to 99%, which proves that the proposed method has good robustness.
    Keywords: improving genetic algorithm; project location; optimising method.
    DOI: 10.1504/IJISE.2020.10039044
  • Effect of mesh phasing on dynamic response of rotate vector reducer   Order a copy of this article
    by Chuan Chen, Hanbing Zhang, Wujiu Pan 
    Abstract: The effectiveness of mesh phasing to suppress certain orders of harmonic responses of RV reducer is investigated with Fourier series method. The lumped-parameter method is used to develop a transverse-torsional dynamic model, which considers key factors such as mesh stiffnesses of involute and cycloidal gears, bearing stiffnesses and support stiffnesses. The Fourier series method is used to solve dynamic response excited by the mesh stiffness. According to characteristics of the central components, each order of harmonic responses belongs to one of three typical types: rotational, translational and planetary component response modes. The typical response mode is related to mesh phasing factor. The law of mesh phasing is revealed by exploring the relationship between suppression of certain harmonic and mesh phasing factor, which is due to inherent symmetrical structure. Finally, the influence of the stiffness and torque on dynamic response is studied. The research provides some referential value for the reduction of vibration and dynamic design of RV reducer.
    Keywords: RV reducer; dynamic response; mesh phasing; influence factor.
    DOI: 10.1504/IJISE.2021.10041580
  • A new hybrid method for optimizing multi-surface problems: DSM method (Power plants of IRAN)   Order a copy of this article
    by Elham Shadkam 
    Abstract: In this paper, a new hybrid method is proposed for optimising multi-response surfaces simultaneously which is a combination of data envelopment analysis and the response surface method. For this reason, the proposed method is called the DSM method. This method not only investigates optimising multi-response surfaces but also considers the efficiency maximisation of decision-making units (DMUs). As a result, the outcome of this method is an optimised set of inputs and outputs with high efficiency of DMUs. DMS considers each DMU as an experiment in the design of the experiment and multi-response surfaces are transformed into a single-response surface, and instead of different response surfaces, an efficiency surface is replaced. Due to the high importance of the electricity industry and energy production, power plants, which are responsible for a very important part of electricity generation, have to increase the efficiency of their activities in order to make better use of resources. In this regard, the proposed method is implemented to account for the efficiencies of the power plan of Iran, and determine the optimum factors for the construction of a new one.
    Keywords: data envelopment analysis; DEA; response surface method; RSM; efficiency; optimisation; power plant.
    DOI: 10.1504/IJISE.2021.10039272
  • Productivity Enhancement in Caravan Manufacturing: An Organisational Resource Centric Approach   Order a copy of this article
    by Ngwenya Rakobela, Michael Ayomoh, Thomas Munyai, Stephen Nyakala 
    Abstract: This paper has identified organisational factors and resources that contributes to low productivity and poor quality in caravan manufacturing. Eight productivity enhancing factors directly linked to caravan manufacturing process were identified and a framework to enhance productivity of caravan manufacturing was proposed. The dataset utilised in this research were obtained from a qualitative data gathering process premised on system observation. The supplier input process output customer (SIPOC) and value stream mapping (VSM) were both utilised to assess the current as-is productivity level of the case-study system. The same tools were deployed for identification of waste generating processes in the system, conduct of analysis for reduction of work in progress inventory and lead times associated with non-value adding activities. The analysis conducted herein was carried out through content and comparative analysis methods using MS Excel 2013 software while the causes and effect matrix was used for data measurement on a prescribed rating scale.
    Keywords: caravan manufacturing; organisational resources; productivity; quality enhancement.
    DOI: 10.1504/IJISE.2021.10039311
  • A prospect secondary goal model for ranking DMUs in DEA-R   Order a copy of this article
    by Simin Tohidnia, Ghasem Tohidi 
    Abstract: This paper presents a prospect DEA-R model by combining the DEA-R model and prospect theory that can be used to evaluate DMUs in decision making under risk. In this study, the proposed model is used as a secondary goal model to determine a unique set of weights in the evaluation of DMUs by cross-efficiency method and thus the psychological behaviours of experts are incorporated in the evaluations. In fact, the present paper introduces an approach for ranking DMUs in DEA-R that can be useful in decision making under risk and especially for decision makers who are familiar with ratio analysis. An empirical application also will be presented to illustrate the applicability of the proposed model.
    Keywords: data envelopment analysis; DEA; DEA-R; secondary goal model; prospect theory; cross-efficiency.
    DOI: 10.1504/IJISE.2021.10039541
  • A system dynamic to reforming of the health care sector in the Indonesian National Health Insurance System program   Order a copy of this article
    by Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto 
    Abstract: National Health Insurance System (NHIS) was established by the Indonesian Government to ensure the health needs of its people. However, the programme encountered many obstacles due to inefficiencies caused by changes in people’s behaviour. The aim is to identify key factors, evaluate and plan further policies using Indonesian data from 2014 to 2018. The system’s dynamics approach is used to build a model for determining policy alternatives that only focuses on referral reform and limiting health service coverage. The proposed model was proven correct and then implemented in 2019 to plan a policy solution. The result was limiting healthcare coverage as a short-term strategy, whereas changing tiered referrals to combined referrals could be considered a long-term strategy. However, the success of this strategy will only occur if there is good collaboration between health services and regulations. In addition, it is necessary to improve the structure of healthcare.
    Keywords: system dynamics; simulation; National Health Insurance System; NHIS; patient referral mechanism; financial strategy.
    DOI: 10.1504/IJISE.2021.10039542
  • Estimating the stress-strength parameter in multi-component systems based on adaptive hybrid progressive censoring   Order a copy of this article
    by Akram Kohansal, SHIRIN SHOAEE, Mohammad Z. Raqab 
    Abstract: Under different probability distributions, numerous authors have discussed the estimation of the reliability in a stress-strength model. In this study, we investigate the reliability parameter estimation in multi-component stress-strength models based on the adaptive hybrid progressive censored sample of two-parameter Kumaraswamy distribution in various situations. In this regard, various methods such as the maximum likelihood, approximate maximum likelihood, Lindley’s Bayesian, and Metropolis-Hastings methods are used to estimate the reliability parameter in this structure. Furthermore, the corresponding confidence intervals, bootstrap confidence intervals, and highest posterior density credible intervals of the multi-component reliability parameter are then established. Also, simulation studies are represented to evaluate and compare the performance of the proposed methods and one practical dataset to analyse illustrative purposes.
    Keywords: adaptive type-II hybrid censored sample; Bayesian estimation; Kumaraswamy distribution; Monte Carlo simulation; multi-component stress-strength model; progressive censored sample.
    DOI: 10.1504/IJISE.2020.10039570
    by Roman Felipe Bastidas Santacruz, Roberto Rocca, Elisa Negri, Luca Fumagalli 
    Abstract: Among the different smart technologies with the highest digitalisation capacity for manufacturing environments, distributed ledger technologies (DLT) has the potential to support one of the main challenges to be faced in the new environment created by the Industry 4.0 paradigm, i.e., the interchange of data through the supply chain. DLT enhances data immutability and transparency and offers new possibilities of interactions and business models to the new industrial networks, allowing a trustable horizontal and vertical data flow between different organisations. Although these possible improvements are in sight, the approach and characteristics that can make the technology suitable with the I4.0 paradigm, are not yet well-defined, and in some cases puzzling for industry managers. In this paper, possible applications, features of DLTs and its available types are reviewed and analysed, giving a clear definition of the most relevant characteristics that these technologies can offer to manufacturing industry.
    Keywords: distributed ledger technologies; DLT; blockchains; Industry 4.0; manufacturing applications; direct acyclic graph; smart manufacturing; networks.
    DOI: 10.1504/IJISE.2021.10039693
  • Data-Driven Prognostic Framework for Remaining Useful Life Prediction   Order a copy of this article
    by Asmaa Motrani, Rachid Noureddine 
    Abstract: Industrial prognostic, based on data resulting from a monitoring up stream, is considered as a crucial stage in making complex industrial systems more reliable. The purpose of the industrial prognostic is to predict the future state of the monitored system, and to give, more specifically, an estimation of its remaining useful lifetime (RUL). Among the used approaches, data-driven prognostic is the most promising when dealing with multitude heterogeneous data. The aim of this work is to present a data-driven prognostic framework implementation, where the RUL is determined through the association of statistical and artificial intelligence methods. This framework is based on the relevance vector machine (RVM) technique to build the predictive degradation model in the offline part, and on the similarity-based interpolation (SBI) technique for the prediction of the remaining useful life in the online part. The different steps of the proposed framework are described and implemented through a case study.
    Keywords: prognostic and health management; PHM; data-driven prognostic; sparse Bayesian learning; SBL; relevance vector machine; RVM; sparse Bayesian interpolation; SBI.
    DOI: 10.1504/IJISE.2021.10039700
  • Sustainability in Indian Manufacturing Sector: An empirical study on challenges   Order a copy of this article
    by Biswajit Mohapatra, Aneesh Kuruvilla, Deepak Singhal, Sushnata Tripathy 
    Abstract: Sustainability is an inexorably pertinent issue in all nations for building a cleaner, greener and prosperous industry around the globe. The concerned research is to build a model delineating the factors affecting sustainability and their degree of hindrance in the Indian industrial paradigm. The authors, through extensive literature review and expert opinions, have identified the factors affecting sustainability in India and then have attempted to structure a model by taking the seven major factors as constructs to the central construct called sustainability challenges. The degree of hindrance has been elucidated in the model and suitable inferences having a high future impact are drawn as a consequence of this rigorous effort. The multivariate statistical analysis method of structural equation modelling (SEM) has been utilised to capture the solution of the problem. The results of the research have a meaningful set of insights about the Indian chapter of sustainability in industries.
    Keywords: sustainability; challenges; structural equation modelling; SEM; manufacturing.
    DOI: 10.1504/IJISE.2021.10039817
  • An assembly process simulation method in immersive virtual reality environment   Order a copy of this article
    by Hui Zhang, Biao Yan, Liling Xia, Qiucheng Wang 
    Abstract: Virtual assembly process simulation is difficult to simulate the real assembly process completely due to the imperfection of haptic and force feedback. To solve this problem, a novel assembly process simulation method is proposed in this paper. Firstly, the rough and exact placement stages were divided according to the actual assembly process, and then a series of judgment rules were formulated to determine their assembly completeness according to the differences of geometric features and assembly methods of different parts. Meanwhile, to let users feel the constraint effect of contacts on part motion in the virtual environment without force feedback, a heuristic analysis method is introduced. The results show that the proposed method can better reflect the uncertainty of human’s actual assembly operation compared with the method based on geometric constraints, and it can better meet the needs of assembly analysis of mechanical products.
    Keywords: virtual assembly; virtual environment; force feedback; heuristic analysis method; constraint effect.
    DOI: 10.1504/IJISE.2021.10039818
  • Do models with individualised risk and socially responsible investment objectives fare better than the generic risk-reward Markowitz model? A comparative analysis using JSE Limited   Order a copy of this article
    by Melissa Van Niekerk, Nadia M. Trent 
    Abstract: Existing portfolio selection models select portfolios based on a generic notion of portfolio risk. Two extensions of the Markowitz model are presented, one that matches a portfolio’s risk to the risk appetite of an individual investor, and one that excludes socially irresponsible shares. A comparative test is conducted between these extended models and the Markowitz model using empirical data from JSE Limited. Goal programming and stochastic programming are employed to incorporate the multiple objectives and address stochasticity. The study shows that while differentiating portfolios based on individual risk appetites or excluding socially irresponsible shares did result in different portfolio structures, the future returns were not very different between the generic and individualised models. This paper firstly illustrates the importance of empirical testing to validate portfolio selection models. It secondly suggests that much of the art of investing is not currently captured in portfolio selection models.
    Keywords: portfolio selection; stochastic programming; goal programming; investment risk measure; JSE Limited; Markowitz.
    DOI: 10.1504/IJISE.2021.10040039
  • Two-Wheeler Authorised Service Centre: A System Dynamics Study of “Limits to Growth” Archetype   Order a copy of this article
    by Virupaxi Bagodi, BISWAJIT MAHANTY 
    Abstract: Two-wheelers have become a common mode of transportation India, 1/3rd households own them and more than 225 million two-wheeler move on the roads. The corresponding growth in two-wheeler services is not observed. The purpose of the paper is to investigate the reasons for stagnation in the growth of services despite better service quality and experienced service personnel in a two-wheeler service centre. It is also intended to demonstrate the short comings in decision-making, using the limits to growth archetype, that nothing grows unabated and in a complex system, compensating feedback loops slow down the growth. The data from the service centre of a premier manufacturer was gathered for three months during 2019. A system dynamics model is developed iteratively for the problem the entrepreneur is facing. Policy experimentations are carried out. The results corroborate that just pushing the growth engine is inadequate for sustainable growth and compensatory feedback loops inhibit the growth of performance measures. Results also indicate that starting the business with higher service capacity and adding capacity at appropriate time is vital in a service firm.
    Keywords: limit to growth; service centre; two-wheelers; decision-making; India.
    DOI: 10.1504/IJISE.2021.10040216
  • Identification and generalizability of key causes of challenges in the implementation of IPD contract in construction projects with the perspective of Iran road construction projects   Order a copy of this article
    by Mohammadjavad Nasiri Jahroudi, Mehdi Nani, Ebrahim Safa, Ehsan Sadeh 
    Abstract: Integrated project delivery (IPD) system is one of the new achievements of the construction industry in the field of contracting and project implementation, especially infrastructure projects in the construction industry, which tries to improve the project output by integrating the project team and working together between different factors and elements involved in the project. Despite of many advantages and increasing applications of the IPD contract method revealed in developed countries, there are so much challenges in using that, due to lack of familiarity and sufficient information, in developing countries such as Iran. In this article, after extensive studies and investigations, the most important causes of challenges in the implementation of IPD contract and its generalisability with the nine principles of this type of contract and their correlation with Pearson statistical method were identified. Then, the challenges identified in IPD with methods Friedman were ranked and the most important items were extracted.
    Keywords: generalisability; correlation; causes of challenge; IPD principles; statistical tests.
    DOI: 10.1504/IJISE.2021.10040220
  • Optimizing Patient Revisit Intervals for Virtual and Office Appointments in Chronic Care   Order a copy of this article
    by Xiao Yu, ARMAGAN BAYRAM 
    Abstract: Virtual appointments are cost-effective alternatives to the traditional office appointments where patients receive the required care remotely. Virtual appointments are used to complement or substitute for office appointments due to the limitations on the availability of office appointments. They improve patients’ access to care and provide convenient care for the patients. However, it is challenging to integrate these appointments with traditional appointments and to decide the visit frequency of patients for different types of appointments since these appointments have different effectiveness. In this paper, we consider a clinic that provides both virtual and office appointments in a chronic care setting. We develop an open migration network to simulate the patients’ flow in the clinic system and build mathematical models to investigate the optimal follow-up rates (i.e., revisit intervals) for both virtual and office appointments. With the model developed, more systematic decisions can be made to determine follow-up rates.
    Keywords: virtual appointments; revisit intervals; chronic care; migration network model.
    DOI: 10.1504/IJISE.2021.10040234
  • Research on Cross platform information transmission method of industrial Internet of things based on XML Technology   Order a copy of this article
    by Changhong Zhu, Tianci Pan 
    Abstract: Aiming at problems of large error in data feature extraction and high congestion in the traditional information transmission methods, this paper proposes a cross-platform information transmission method of industrial internet of things based on XML technology. Based on the networked information features of extract, SUM function was used to complete the feature fusion. Then, the XML technology is used to obtain the optimal segmentation of tree, and the fitting training of tree data is carried out to realise the safe storage of information. Then, the information distribution probability is obtained according to the nature of XML file, so as to realise the cross-platform transmission of information. According to the simulation results, it can be seen that: the data feature extraction error of this method is at least 2.1%, the sample data transmission time is always lower than 6 s, and the transmission process congestion is low, which fully proves its effectiveness.
    Keywords: XML technology; industrial internet; SUM function; cross-platform transmission; distribution probability.
    DOI: 10.1504/IJISE.2021.10040357
  • A Decision Support System for Selecting Augmentative and Alternative Communication Devices   Order a copy of this article
    by Eduardo Pérez, Mahima S. Varghese, Amy L. Schwarz 
    Abstract: The goal of this research is to improve access to services for patients in need of augmentative and alternative communication (AAC). The specific aim of this paper is to develop a decision-making model that evaluates an exhaustive list of AAC devices and recommends the best alternative(s) for the patient. The model maximises a best-fit function that considers the patient’s disability profile and the capabilities of each device. Currently, there are multiple private and government companies that offer a large variety of devices targeting patients in need of AAC. However, the decision-making process of what device to try on the patient is largely based on the health professional’s experience and familiarity with specific companies. The proposed decision-model has the capability of improving patient experience of care by reducing the assessment time required to find the best device.
    Keywords: decision making; augmented and alternative communication; AAC; healthcare; medical devices.
    DOI: 10.1504/IJISE.2021.10040471
  • Safety Requirement Verification of Train-centric CBTC by Integrating STPA with Coloured Petri Net   Order a copy of this article
    by Qian Xu, Junting Lin 
    Abstract: Train-centric communication-based train control (TcCBTC) system is characterised by core functions centralised into on-board facilities with simplified trackside equipment. Coloured Petri net (CPN) is one of the classical model checking methods and system-theoretic process analysis (STPA) is a relatively new hazard identification method based on system thinking and control theory. STPA and CPN are mutually complementary because STPA provides the verification basis for CPN while CPN makes STPA’s results written by natural language verifiable. The functional requirements of TcCBTC are analysed first. Secondly, via the assistant analysis tool XSTAMPP 2.0, the hierarchical control structure is built and the refined unsafe control actions are obtained to generate the safety requirements. Thirdly, CPN models are constructed for verifying the basic properties and the safety. Results show that the potential unsafe control paths can be identified by the proposed method on the system level and the dependence severity on the manual analysis is considerably reduced.
    Keywords: train-centric CBTC; system-theoretic process analysis; STPA; coloured Petri net; CPN; safety requirements verification; unsafe control actions.
    DOI: 10.1504/IJISE.2021.10040903
  • Service Level and Profit Maximization in Order Acceptance and Scheduling Problem with Weighted Tardiness   Order a copy of this article
    by Mohammad Yavari, Amir Hosein Akbari 
    Abstract: Traditional order acceptance and scheduling (OAS) problem focused on profit optimisation and the number of accepted orders has been only regarded as a constraint in the OAS model in a few research studies. The current paper investigates a bi-objective OAS problem to maximise profit and service level. There are two categories of regular and special orders in a single-machine environment. We have proposed a mixed integer linear program using goal programming. Due to the NP-hard nature of the problem, we have developed a simulated annealing-based heuristic to solve the problem, and a lower bound to assess its performance. Both single objective and bi-objective versions of the problem have been studied. Computational experiments demonstrate the ability of the proposed heuristic. The advantages and disadvantages of the proposed bi-objective OAS problem are discussed. Also, the relation between service level and profit objectives is studied in both problems with and without special orders.
    Keywords: order acceptance and scheduling; OAS; service level; simulated annealing-based heuristic; mixed-integer linear programming; MILP; goal programming; bi-objective; lower bound.
    DOI: 10.1504/IJISE.2021.10041481
  • Insightful Implementation of Lean Tools to Cultivate Lean Culture in Small Scale Manufacturing Organization a case study   Order a copy of this article
    by Jaydeepsinh Ravalji, Shruti Raval, Gulamkhwaza Qureshi, Himadri Shukla 
    Abstract: Small and medium-scale organisations are the backbone of the Indian manufacturing sector. Awareness and proper use of the Lean approach can improve their productivity. This paper demonstrates insightful use of some of the Lean tools to a small subcontractor organisation; for improvement in its current process with less expenditure. The second objective was to develop an attitude among production people for waste-free practices through innovative ideas. To achieve these objectives, the current state VSM was prepared to identify wastes in the process. Kaizen, Pacemaker, PEEP, and two-Bin Kanban system were used to achieve the ideal process. By implementing these tools, the total cycle time for one rotor assembly is reduced by 37.12%, the total lead time is reduced by 7.1%, and inter-departmental material movement per day is reduced by 37.5%. This paper will motivate researchers and practitioners to develop specific but effective solutions with knowledge of Lean philosophy.
    Keywords: lean manufacturing; 5S; value stream mapping; VSM; Kaizen.
    DOI: 10.1504/IJISE.2021.10041486
  • Cost Optimality of an erratic Geo^{X}/G/1 Retrial Queue under J-vacation scheme using Nature Inspired Algorithms   Order a copy of this article
    by Radhika Agarwal, Shweta Upadhyaya, Divya Agarwal, Sumit Kumar 
    Abstract: In this article, we have explored a GeoX/G/1 model with Bernoulli feedback wherein the clients that enter and find the system to be busy, halt for a while prior to attempting again to enter the system. The server is erratic and can take utmost J-vacations regularly unless one client appears in the virtual track (orbit) again on returning from vacation. Also, the server is sent for repair on an urgent basis as soon as it breaks down. Using the probability generating function technique, the system size distribution of the server during busy, breakdown, vacation state and orbit size along with some performance measures have been derived. These derived quotients are then visualised and validated with the help of tables and graphs. Further, the cost analysis of the model is carried out and the optimal cost for the system is obtained. We have used direct search method, particle swarm optimisation (PSO), artificial bee colony (ABC) and cuckoo search (CS) techniques for the comparative study and presented the graphs for the convergence of these techniques.
    Keywords: discrete-time; starting failure; normal breakdown; J-vacation; Bernoulli feedback; cost optimisation; direct search; particle swarm optimisation; PSO.
    DOI: 10.1504/IJISE.2021.10041559
  • Manufacturing Management of Productivity in the Steel Industry Using System Dynamics Modelling and Statistical Evaluation   Order a copy of this article
    by Thomas Munyai, MAKINDE OLASUMBO, Michael Ayomoh, Alufeli A.E. Nesamvuni, Boitumelo B.I. Ramatsetse 
    Abstract: This paper has identified and analysed various drivers capable of influencing the level of productivity in steel manufacturing. The South African Steel Manufacturing Industries (SASMI) was used as a case study for this research. In order to achieve this, a comparative analysis of factors that could influence the productivity of SASMI was conducted using the exploratory factor analysis. Next was the creation of an integrated network of the systemic factors and lastly, the development of a system dynamics model for insight into the sensitivity of productivity dynamics per factor over a period of 30 months. Multiple regression analysis (MRA) was used to establish the relationship between productivity and its drivers. The results of the MRA, showed that competitiveness in terms of (production strategy, speed, cost, quality monitoring strategy and market share); facility layout and government support with weights of 0.319, 0.249 and 0.153, respectively, are critical to the productivity of SASMI.
    Keywords: productivity; system dynamics; steel manufacturing; manufacturing management; multiple regression analysis; MRA.
    DOI: 10.1504/IJISE.2021.10041636
  • Design of a mathematical model and a simulation-optimization approach for master surgical scheduling considering uncertainty in length of stay, demands and duration of surgery   Order a copy of this article
    by Mohammad Ebrahimi, Arezoo Atighehchian 
    Abstract: In this research a master surgical scheduling problem in conditions of uncertainty of demand, duration of surgery and length of patients’ stay is studied. First, an MIP model is developed in which the length of patients’ stay is considered probabilistic. Then, allowing for uncertainty in demand, a robust model is presented. Finally, a simulation-optimisation approach is developed in which three parameters are considered as uncertain. In this approach, the Grey Wolf and genetic algorithms are designed as the optimisation, and the Mont Carlo simulation is used in the simulation module. The results show that the maximum gap in the comparison of the simulation-optimisation algorithms and the lower-bound solution of the mathematical models in small-scale problems is only 9.36% while the algorithms are much faster. In larger-scale problems, the average improvement percentage of the proposed approach with the Grey Wolf optimisation module as compared to the genetic algorithm module is 2.93%.
    Keywords: master surgical scheduling; MSS; simulation-optimisation approach; mixed integer programming; uncertainty; robust optimisation.
    DOI: 10.1504/IJISE.2021.10041644
  • Toward Smart Manufacturing Systems incorporating Reconfiguration Issues   Order a copy of this article
    by Ibrahim H. Garbie, Abdelrahman I. Garbie 
    Abstract: Nowadays, Industry 4.0 will become urgent to be implemented in most of the developed countries, although it is still mainly conceptually. As there are three different aspects consisting of Industry 4.0 (I4.0) such as digital systems, biological systems, and physical systems, most of the research published works were focused on mainly the first one. The smart manufacturing system (SMS) is not an invention, although it is representing the heart of I4.0. The SMS is a rebirth of a new version and innovation of production systems taken into consideration reconfiguring the existing manufacturing systems through adding machines with sensors, actuators, and control architectures for achieving the ultimate goals of I4.0. There are many challenges when reconfiguring these systems as an essential requirement to implement I4.0, representing the degree of individual system complexity, reconfigurable machines, material handling systems, system layout; competitive manufacturing strategies; and leanness agility), and embedded systems (cyber-physical systems). In this paper, a new perspective of reconfiguring manufacturing systems will be figured out, and the reconfigurability level toward I4.0 will be presented.
    Keywords: Industry 4.0; smart manufacturing systems; SMSs; reconfiguration.
    DOI: 10.1504/IJISE.2021.10041796
  • An aircraft position updating based algorithm for single runway scheduling with normal and alternate aircrafts   Order a copy of this article
    by Hong-Da Dou, Feng Wang, He Pan, Yi-Fan Wang, Tsui-Ping Chung 
    Abstract: This paper investigates the problem of scheduling normal and alternate landing aircrafts at a single runway on Changchun Longjia International Airport. Usually, if the destination airport does not satisfy the landing conditions, then the aircraft has to use an alternate airport. Both normal and alternate landing aircrafts arrive at a fixed time window. Meanwhile, safety interval of adjacent landing aircrafts depends on their sizes. An integer programming model is proposed to minimise the landing completion time. Since the problem is NP-hard, an aircraft position updating based algorithm is proposed. To evaluate the performance of the proposed algorithm, a real case from Changchun Longjia International Airport and randomly generated problem instances are tested. The results show that the proposed algorithm has a better performance than the first-come first-served order and the landing constraints-based heuristic algorithms.
    Keywords: normal landing aircrafts; alternate landing aircrafts; single runway; fixed time window; safety interval; landing completion times.
    DOI: 10.1504/IJISE.2021.10041834
  • Modeling Customer Demand for Mobile Value-Added Services: Non-Stationary Time Series Models or Neural Networks Time Series Analysis?   Order a copy of this article
    by Mohammad Hossein Vaghefzadeh, Behrooz Karimi, Abbas Ahmadi 
    Abstract: The present research applies two different modeling approaches to evaluate the historical demand for a special mobile value-added service (VAS) that is offered and delivered to airline customers. The first method is deterministic and includes non-stationary time series models that cover both mean and variance fluctuation, as well as seasonality effect, in the dataset. The second method is a metaheuristic approach in the form of artificial neural network time series analysis (ANN-TSA). These methods are used to evaluate the power of each category and to choose the best model based on appropriate criteria. The results show that non-stationary time series models outperform ANN-TSA, as indicated by the smaller number of errors in the simulation of the demand dataset.
    Keywords: time series; analysis; non-stationary; artificial neural network; mobile value-added; seasonal effect; demand; forecasting.
    DOI: 10.1504/IJISE.2021.10041835
  • Investigating the challenges faced by Indian Automotive Industry for adopting technology organically   Order a copy of this article
    by Mudita Dixit, Gopakumaran Thampi 
    Abstract: The Indian automobile sector is the sixth-largest producer of automobiles globally in terms of worth and volume. India has a steady trade deficit of US$ 2 billion in auto components every year. This paper critically examined reasons for India lagging in technology adoption and transfer organically in different sectors (OEM, large, medium and small enterprises) of the automotive industry (AI). A survey was conducted on 272 enterprises located in the western region of India. The result shows that the high purchasing cost of technology, lack of awareness of IT tools, availability and retainability of skilled workforce are critical issues for small and medium enterprises compared to large enterprises and OEMs. This study determines the role of government policies, state policies, and proactive measures to contribute to AIs fortune. It is observed that AI shall replicate success stories of the Indian IT industry in terms of global reach and quality arbitrage offering to the export market.
    Keywords: advanced manufacturing technology; R&D; Indian automotive sector; latest technology adoption; original equipment manufacturer; OEM.
    DOI: 10.1504/IJISE.2021.10041846
  • Implementing Lean-Kaizen for Manufacturing Operations Improvement: A Case-Study in Plastics Industry   Order a copy of this article
    by Tareq Issa 
    Abstract: Lean manufacturing is concerned with the implementation of several tools and techniques that aim for the continuous elimination of waste in order to achieve competitive production systems. This research addresses the implementation of lean-kaizen concept and related techniques as part of a framework to achieve lean operation in a small-medium sized plastic bag manufacturing enterprise. The primary goal is to implement the lean-kaizen methodology to eliminate/reduce cycle time waste for the material mixing and roll formation processes in the manufacturing operation under study. The current state map was constructed, the processes identified for cycle time reductions were considered as well as the future state map was developed that served as a guide for lean-kaizen implementation. Root causes of waste were identified and two kaizen events were proposed as solutions. In the first kaizen event, the poka-yoke technique was used to automate the mixing process and eliminate variation and, for the second kaizen event, process standardisation was achieved in the roll formation process. As a result of implementing kaizen events, total cycle time was reduced and, consequently, productivity performance has increased to 94.7%.
    Keywords: lean-kaizen concept; kaizen event; cycle-time reduction; plastic bags industry; value stream map.
    DOI: 10.1504/IJISE.2021.10042029
  • A Tutorial on Optimization involving David Ricardo Theory on Comparative Advantage   Order a copy of this article
    by Tapan P. Bagchi, R.P. Mohanty, Surajit Sinha 
    Abstract: Ricardo (1821) showed how two countries producing two different goods using a single endowed factor of production (the 2-2-1 situation), but operating with unequal efficiency, can benefit if they freely barter certain parts of their production, even if one is more efficient in producing every good. When done, such trade produces more goods in total using the same amount of total resource, rather than each producing enough goods only for own consumption, as in autarky. Ricardo showed that global benefits (measured in units of total goods produced) can accrue if each country specialises
    Keywords: comparative advantage; factor of production; free trade; linear programming; international trade; optimisation; Ricardo’s principle of trade.
    DOI: 10.1504/IJISE.2021.10042185
  • Prediction of uncertainty risk factors in engineering management system based on improved decision tree   Order a copy of this article
    by Rong Tang, Guoxiong Zhang, Yunxia Li 
    Abstract: In order to overcome the problem of low efficiency of the current prediction method for uncertainty risk factors in engineering management system, this paper proposes a prediction method for uncertainty risk factors in engineering management system based on improved decision tree. In this method, the reason model (accident causal model of complex system) and software, hardware, environment and livewar (SHEL) model are used to analyse the uncertainty risk factors in engineering management system, and the prediction system of uncertainty risk factors is established. The fuzzy clustering analysis method is used to judge the expert weight of risk factors, and the improved decision tree algorithm combined with the judgment results is used to predict the uncertainty risk factors in engineering management system. The simulation results show that the proposed method can reduce the prediction error rate by 1.5% in the following time.
    Keywords: engineering management system; uncertainty; risk factors; improved decision tree; fuzzy clustering; prediction.
    DOI: 10.1504/IJISE.2021.10042297
  • A Machine Learning Algorithm for Scheduling a Burn-in Oven Problem   Order a copy of this article
    by Mathirajan M, Sujan Reddy, Vimala Rani M, Dhaval P 
    Abstract: This study applies artificial neural network (ANN) to achieve more accurate parameter estimations in calculating job-priority-data of jobs and the same is applied in a proposed dispatching rule-based greedy heuristic algorithm (DR-GHA) for efficiently scheduling a burn-in oven (BO) problem. The integration of ANN and DR-GHA is called as a hybrid neural network (HNN) algorithm. Accordingly, this study proposed eight variants of HNN algorithms by proposing eight variants of DR-GHA for scheduling a BO. The series of computational analyses (empirical and statistical) indicated that each of the variants of proposed HNN is significantly enhancing the performance of the respective proposed variants of DR-GHA for scheduling a BO. That is, more accurate parameter estimations in calculating job-priority-data for DR-GHA via back-propagation ANN leads to high-quality schedules w.r.t. total weighted tardiness. Further, proposed HNN variant: HNN-ODD is outperforming relatively with other HNN variants and provides very near optimal/estimated solution.
    Keywords: dispatching rules; semiconductor manufacturing; greedy heuristic algorithm; GHA; artificial neural network; ANN; optimal solution; estimated optimal solution.
    DOI: 10.1504/IJISE.2021.10042607
  • Use of heuristic methods for the optimization of truck loading in a steel company   Order a copy of this article
    by Andre Luis Korzenowsk, Felipe Kirsch Hoerbe, Taciana Mareth, Lucas Schmidt Goecks 
    Abstract: The correct layout of goods, objects or cargo, in the container’s available space is considered a complex task. The study was motivated by the need to implement a solution to optimise container use in a steel industry company in the South of Brazil. This article has contributed to synthesising research on the three-dimensional container loading problem, highlighting classifications, constraints, and algorithms used in its resolution. A framework is presented and may be used as a road map for practical implementation as used in this research. As a practical contribution, this article presents several instances of one actual case application. Results showed reducing of formatting loads processing time in comparison with the traditional company approach.
    Keywords: operational research; three-dimensional; container loading problem; CLP; steel industry.
    DOI: 10.1504/IJISE.2021.10042608
  • An Innovation Ontology for Idea Forecasting and Measurement   Order a copy of this article
    by Andrew N. Forde, Mark Fox 
    Abstract: Before managers are able to forecast the utility of an idea, there must be a common definition and basis for measuring the potential radicalness of an idea. In this paper, we introduce an ontology to represent an innovation and derive properties that can be used to define and measure an ideas potential to be classified as a radical or incremental innovation. Our proposed ontology captures the concepts of an incremental or radical innovation, and further concepts to support the grouping of innovations. We begin with an extensive review of the literature and identify the categories of innovation, from this group we apply competency questions that allow us to define properties that are the basis for valuing an ideas utility, and classifying an innovation.
    Keywords: innovation management; ontology; semantic web; open innovation; radicalness; incrementalness; innovation properties; innovation categories.
    DOI: 10.1504/IJISE.2021.10042662
  • Inventory management of manufacturers with yield uncertainty and lateral transshipment   Order a copy of this article
    by Arash Ashjaee, Mohammadali Pirayesh, Farzad Dehghanian 
    Abstract: This article deals with the issue of inventory management of one identical product in a manufacturers network. Manufacturers use lateral transshipments between each other in response to uncertainties in yield and demand to maximise the total profit. The demand of each manufacturer is considered random as a non-identical continuous probability distribution and their corresponding yield follows some possible scenarios. The objective of our model is to determine the optimal production amount and lateral transshipments in order to maximise the total profit considering the proceeds from sale of goods and salvage of remaining product and the cost of production, lateral transshipments, and shortages. The problem is modelled as a nonlinear constrained programming and the optimal solution is obtained by Karush-Kuhn-Tucker approach. Sensitivity analysis of uncertainty parameters based on a numerical example showed that the utility of using lateral transshipment policy increases with increasing the uncertainty in production yield.
    Keywords: inventory management; yield uncertainty; lateral transshipment.
    DOI: 10.1504/IJISE.2021.10042971
  • Risk Warning Method of Computerized Accounting Information Distortion Based on Deep Integration Model   Order a copy of this article
    by Wenyuan Chen 
    Abstract: In order to improve the early warning accuracy of accounting information distortion risk and reduce the resource occupancy rate in the early warning process, this paper designs a deep integrated model-based computerised accounting information distortion risk early warning method. The distortion risk identification model is constructed to avoid the interference of invalid information and reduce the resource occupancy rate. Then the quantitative index is used to improve its effectiveness and improve the accuracy of the subsequent warning. Then the deep integration model is used to judge whether there is distortion node in the current computerised accounting information, so as to complete the high precision early warning of distortion risk. Simulation results show that the warning accuracy of this method is always above 0.9, and the resource occupancy rate of the warning process is less than 40%, which proves that this method achieves the design expectation.
    Keywords: computerised accounting information; index quantification; distortion risk identification; risk warning; deep integration model.
    DOI: 10.1504/IJISE.2021.10043036
  • Integrated Scheduling and Vehicle Routing at Cross-dock Distribution Centre: A Simulated Annealing Approach   Order a copy of this article
    by Shikhar Saxena, Rajesh Piplani 
    Abstract: Cross-docking is a popular strategy for distributing products with short shelf-life that must be delivered within their pre-specified time windows to customers. Cross-docks receive shipments from suppliers which are stored in a temporary storage area before being consolidated and transferred to outbound vehicles for delivery to customers. This research tackles the joint problems of vehicle routing and scheduling at the cross-dock, along with product consolidation, by means of a mixed-integer programming model with the objective of minimising the total cost of operations. Our approach does not pre-cluster customers into zones and allows vehicles to deliver in less than truckload. To solve real-life sized problems, we develop simulated annealing algorithms which can solve the instances in 2 to 3 hours, achieving close to optimal solutions, making them suitable for decision support at cross-dock distribution centres, which process dozens of vehicles and deliver to hundreds of customers daily.
    Keywords: cross-docking; routing and scheduling; delivery window; meta-heuristic; product consolidation; simulated annealing.
    DOI: 10.1504/IJISE.2021.10043156
  • Copper Futures Hedging based on Markov switching approach   Order a copy of this article
    by Jiaxuan Chen 
    Abstract: This paper selects the daily closing spot and futures prices of copper in China’s market from May 5, 1995 to February 28, 2020, and then proposes a two-regime bivariate Markov regime-switching model, DCC-GARCH, CCC-GARCH and the OLS model to estimate their time-varying minimum variance hedging ratio and hedging performance for comparison both in- and out-of-sample. The empirical results show that, whether in- or out-of-sample, the two-regime bivariate Markov regime-switching model can provide more detail depiction of dynamic correlation between spot and futures, and outperforms the others for hedging performance. Next is the DCC-GARCH model. CCC-GARCH model and the OLS model have similar performance. Besides, the rolling-window method can make the changes more obvious in the correlation of financial assets, which helps to estimate the time-varying optimal hedging ratio in the fast-changing market.
    Keywords: dynamic futures hedging; Markov regime-switching model; DCC-GARCH.
    DOI: 10.1504/IJISE.2021.10043159
  • New mechanism of credit risk control in order agriculture   Order a copy of this article
    by Dongwei Shi 
    Abstract: The bilateral default rate of farmers and companies is usually high in contract farming. Inspired by the rule of
    Keywords: contract farming; bilateral default risk; mark-to-market.
    DOI: 10.1504/IJISE.2021.10043399
  • IoT enabled smart window for controlling brightness: - A perspective of heat transfer rate   Order a copy of this article
    by Awais Kazi, Nikhil Shinde, Sumeet Mujumdar, Tejas Kulkarni, Prathamesh Potdar 
    Abstract: In a competitive environment, organisations are focusing on the energy-efficient smart system to reduce the expenses related to energy consumption and a comprehensive literature survey shows that windows are significant sources of heat and light in an enclosed space, which increases the load on air conditioner systems to maintain the comfortable conditions inside the room. There is a need to develop IoT enabled smart window for controlling heat and light in this context. In this study, suitable devices and sensors are identified based on a systematic literature survey to develop the IoT-enabled smart window. The experimental setup is also developed to evaluate the heat flow and luminosity inside the closed room. It has been observed that the maximum temperature recorded in the room in the range of 29
    Keywords: polymer dispersed liquid crystal; PDLC; internet of things; IoT; smart window; heating; ventilation; and air conditioning; HVAC.
    DOI: 10.1504/IJISE.2021.10043481
  • E-commerce logistics provider selection based on multi-criteria decision-making approach with uncertain information   Order a copy of this article
    by Kejia Chen, Jin-Hua Zhang, Yi-xin Lan, Ping Chen 
    Abstract: Logistics provider selection is a multi-criteria decision-making problem faced by e-commerce companies. Considering the complexity of the problem and the uncertainty of the decision information, an integrated approach of GTOPSIS is proposed for evaluating and selecting the most suitable logistics provider. The GTOPSIS approach integrates the three-parameter interval grey number (T-PIGN) into the technique for order preference by similarity to ideal solution (TOPSIS). It allows decision-makers to use T-PIGN to represent the performance of the alternatives which can retain and utilise the original uncertain assessment information of alternatives to the greatest extent. Besides, the PERT distribution is adopted to weight the three parameters of T-PIGN. A real-life case study is presented to demonstrate the practicality and effectiveness of the GTOPSIS approach.
    Keywords: multi-criteria decision-making; MCDM; logistics provider selection; interval grey number; TOPSIS.
    DOI: 10.1504/IJISE.2020.10043567
    by Samson Akindele, Olusegun Akanbi, Feyisayo Akinwande, Joshua Ade-Omowaye 
    Abstract: As a result of scarce information regarding the impact of work-related musculoskeletal complaints (WMSCs) in the Nigerian steel industry, this research investigates the frequency of complaints in the various body regions. Subsequently, the relationship between WMSC and the essential worker’s characteristics (age, work tenure and weight) and working posture were addressed. The frequency of complaints of the working population was collected and accessed using the Nordic musculoskeletal questionnaire (NMQ). The active stance of the workers was analysed using the rapid upper limb assessment (RULA). The results from NMQ showed a significant relationship between complaints of the upper and lower back regions among the workgroups. Significantly, there exists a strong correlation among workers characteristics with WMSC. Older workers complained more about specific body regions than the relatively younger workers. The RULA showed that the maintenance department workers had the most significant postural risk, followed by the melting section.
    Keywords: posture; casting; productivity; rapid upper limb assessment; RULA; musculoskeletal complaints; discomfort; safety; steel industry.
    DOI: 10.1504/IJISE.2021.10043568
  • A Case Study on the Design and Implementation of a New Product for Infants Learning to Walk   Order a copy of this article
    by Hu Shan, Jia Qi, Wang Yuqing, Fu Kaijie, Zhang Liyan, Guo Min, Guo Weiqi 
    Abstract: In order to solve the problem of the poor user experience and low satisfaction of infants and parents caused by insufficient research into existing products for toddlers. Based on the design and development process, this research takes pre-existing dual user research as its core and uses literature research, a focus group and other methods to determine dual user needs, as well as the Kano model to determine the demand attribute classification of the mixed methods of qualitative and quantitative research. Then, in this research, we design a system to help infants learn to walk that conforms to the characteristics of an infant’s physical and psychological development and meets the needs of parent users. The system can guide an infant to actively learn to walk through a multisensory interactive approach; meanwhile, parents’ fatigue and anxiety regarding children walking will be relieved during this period. In the final stage of this research, we design a product prototype to test the usability of the system. The research method can also be applied to other types of product design, and the design cue map obtained through user research has reference significance for other infant products.
    Keywords: infant; toddler; product design; user research.
    DOI: 10.1504/IJISE.2021.10043976
  • Asymptotic analysis of a Bernoulli Vacation non markovian Queuing system in Air traffic control system   Order a copy of this article
    by Radha S, S. Maragathasundari, P. Manikandan 
    Abstract: We examine a single server queue arriving with Poisson batches of varying sizes. When the system starts the service, it provides service to all the arriving customers on a first come first served basis. Before the first service starts after each system downtime, the server provides general services to the client for a specified time of random duration, known to be a set-up time stage. If the server is affected by random crashes, a delay time occurs before the commencement of repair process. If there are no clients in the queue after the service is complete, the server takes a Bernoulli vacation. Two new parameters, reneging and restricted admissibility happen during the process of vacation and repair process respectively. For the defined queuing issue, we find the length of the duration of the steady state of different states of the system according to the probability generating function. Other queue performance metrics are also exported. In addition, the disposal is legalised through a digital scheme and graphic representation. This model means that supervisors are aware of the structural difficulties of the client-server framework and the basic rules of investigation.
    Keywords: setup time; service interruption; repair process; restricted admissibility; Bernoulli schedule; reneging; supplementary variable technique.
    DOI: 10.1504/IJISE.2021.10043978
  • An integrated Fuzzy QFD approach to leagile supply chain assessment during COVID-19 crisis   Order a copy of this article
    by Fadoua Tamtam, Amina Tourabi 
    Abstract: The COVID-19 crisis has severely disrupted the Moroccan automotive production. This pandemic has weakened automotive supply chain; it faced a fall in demand and reduction in sales. Consequently, the automotive industry developed their production capabilities through constant innovation in resource reduction (leanness) while responding rapidly to demand changes (agility). A combination of lean-agile supply chain leads to obtain competitiveness in a time and cost effective manner. Successful implementation of leagile supply chain requires evaluation of criteria and attributes. To this end, the purpose of this paper is to propose a leagility evaluation framework using fuzzy quality function deployment approach. As a result, order guidance has been taken as the most important capability of automotive supply chain. E-fulfilment logistic has been considered as the most important enabler to gain supply chain leagility.
    Keywords: supply chain leagility; automotive industry; fuzzy quality function deployment; FQFD; leagile drivers; leagile capabilities; leagile enablers.
    DOI: 10.1504/IJISE.2021.10044277
  • New approaches for the Prize-Collecting Covering Tour problem   Order a copy of this article
    by FRANCISCO CLIMACO, Luidi Simonetti, Isabel Rosseti, Pedro Henrique Gozales 
    Abstract: In this paper, we consider the prise-collecting covering tour problem (PCCTP), which intends to find a minimum cost tour for travelling teams that grant assistance to people located far from urban centres. We develop a branch-and-cut algorithm, some valid inequalities, and a new set of reduction rules as exact approaches. We also present a hybrid heuristic that combines a state-of-the-art heuristic for the PCCTP with integer programming techniques. Computational experiments showed that the exact approaches found several new optimal solutions while reducing CPU time, and the hybrid heuristic was able to match or improve the solution quality for many instances, along with a significant reduction of running time.
    Keywords: prise-collecting covering tour problem; PCCTP; greedy randomised adaptive search procedure; GRASP; random variable neighbourhood descent; RVND; hybrid heuristic; reduction rules.
    DOI: 10.1504/IJISE.2021.10044534
  • An Artificial Immune System Algorithm for Solving Stochastic Multi-Manned Assembly Line Balancing Problem   Order a copy of this article
    by Mohamamd Zakaria, Hegazy Zaher, Naglaa Ragaa 
    Abstract: In recent years, there has been an increasing interest in the multi-manned assembly line balancing problem (MALBP). It introduces the concept of assigning more operators at the same station to minimise the line length and to increase the production rate. Most of the previous works did not discuss such problems under uncertainty. Therefore, this paper presents a chance-constrained programming model that considers the processing times of the tasks as normally distributed random variables with known means and variances. The proposed algorithm for solving the problem is an artificial immune system algorithm. To get optimised results from the proposed algorithm, the parameters are tuned using a design of experiments. The computational results show the implementation of the proposed algorithm on 70 problems taken from well-known benchmarks in case that chance probability is equal to 0.95, 0.95, and 0.975.
    Keywords: MALBP; chance-constrained programming; artificial immune system; AIS; Taguchi orthogonal arrays; analysis of variance; ANOVA; Tukey’s HSD test.
    DOI: 10.1504/IJISE.2021.10044535
  • An evolutionary game model for low-carbon technology adoption by rival manufacturers   Order a copy of this article
    by Yuxiang Yang, Ying Xie 
    Abstract: Manufacturers’ decisions on adopting low carbon technology are influenced by many factors, including the consumers’ awareness of low carbon technology and governmental carbon tax scheme. In this research, we considered competition between two rival manufacturers and constructed a demand function that considers carbon emission and price as parameters rather than constraints. We developed an evolutionary game model in bounded rationality space and analysed the game between two manufacturers under four game scenarios. The impacts of consumers’ awareness of low-carbon technologies and governmental carbon tax scheme were clearly demonstrated in the manufacturers’ behaviour strategies towards the adoption of low carbon technology. The research findings offered insights into the level of consumers’ low carbon awareness that stimulates both manufactures to adopt low carbon technology, and the threshold of low carbon awareness that incentivises only one manufacturer to adopt low carbon technology. Meanwhile, authority should enact carbon tax within appropriate range in order to reduce carbon emissions.
    Keywords: low carbon technology; evolutionary game; low carbon awareness; carbon tax.
    DOI: 10.1504/IJISE.2021.10044582
  • Integrated optimisation of the unequal-area facility layout and the flowshop group scheduling problems for a case of the garment industry   Order a copy of this article
    by Sebastian Cáceres-Gelvez, Martín Darío Arango-Serna, Julian Zapata 
    Abstract: The unequal-area facility layout (UAFLP) and the flowshop group scheduling (FSGSP) problems are two important problems in both research literature and industrial applications. The former considers the location of departments with different area requirements within a floor plan. The latter seeks for a sequence of product families and jobs to be processed on groups of machines, called manufacturing cells. In this paper, an integrated approach for optimising both the UAFLP and the FSGSP is presented in the case of a sportswear manufacturing company. A genetic algorithm (GA) is proposed for minimising the sum of the total material handling and the tardiness costs. The results showed that the optimisation process obtained a reduction of 6.69% of the total costs for the proposed alternative, in comparison with the current situation of the case study.
    Keywords: unequal-area facility layout; flowshop group scheduling; genetic algorithm; garment industry; integrated optimisation; case study.
    DOI: 10.1504/IJISE.2021.10044730
  • A Bibliographic Study of Sustainability Research: Exploring Multidimensionality   Order a copy of this article
    by Soumyanath Chatterjee, R.P. Mohanty 
    Abstract: Sustainability has gained prominence as a discipline for academics and professional practitioners. This article presents a bibliographic account and related analysis of research in sustainability between 1990 and 2019. A critical study of different aspects of sustainability requires a multi/interdisciplinary systems approach. Such a study may encompass ecological, economical, and sociological perspectives. For this reason, the bibliometric analysis has covered a wide range of professional disciplines. 183,779 bibliographic entries from SCOPUS were analysed with latent Dirichlet allocation (LDA) to discover different aspects of publications in sustainability. The study showed that all publications can be classified according to 25 topics, showing how sustainability research has evolved and the consequent gaps that need to be filled for the advancement of the research and community of practice. The LDA analysis resulted in creating a topic model that facilitates the automated categorisation of publications regarding sustainability.
    Keywords: sustainability; systematic literature survey; text analytics; latent Dirichlet allocation; LDA; topic model; bibliographic analysis.
    DOI: 10.1504/IJISE.2021.10044764
  • Resonant automotive suspension device detection bench based on fuzzy comprehensive recognition algorithm   Order a copy of this article
    by Xuelian Tian 
    Abstract: Suspension affects the stability, ride comfort, handling stability, safety and other performance of the body. In this paper, the fuzzy comprehensive identification algorithm is introduced into the vehicle resonance suspension device detection. The fuzzy comprehensive identification algorithm is used to identify the vehicle mode, calculate the change of vehicle inertia parameters, and propose a higher damping ratio which has a greater impact on the vehicle identification results. Based on the fuzzy comprehensive identification (FCRA) algorithm, a resonant vehicle suspension device detection platform is proposed, which detects the resonant vehicle suspension device caused by the fault by the change of the fuzzy comprehensive identification coefficient and the required modal parameters of the output. The test results show that the performance of the resonant suspension device test-bed is stable and can meet the needs of the performance test of the vehicle suspension device.
    Keywords: fuzzy comprehensive recognition algorithm; FCRA; resonant automotive suspension device; detection bench; optimisation.
    DOI: 10.1504/IJISE.2020.10033881
  • Robust design optimisation of cutting force and material removal rate in thread turning process   Order a copy of this article
    by Suraj Rane, Amar Dalvi, Sujay Kharat, Raheel Ahmed Kittur 
    Abstract: Thread cutting is the most commonly used method of producing threaded components in small scale industries. Literature review revealed that enough research is not undertaken in optimising thread turning, in spite of it being a widely used method of producing threads. The present work highlights a case from a small scale organisation, manufacturing hexagonal headed bolt with high accuracy in lean environment. The objective was to optimise cutting force and material removal rate, which were indicators of power consumption and productivity, respectively. To obtain optimal levels of input parameters using less number of components, a robust design methodology was used. The input parameters studied are cutting speed, depth of cut and infeed angle, in external thread turning of mild steel. The optimum level of each input variable was found out for minimum cutting forces generated and maximum material removal rate. Significant improvement in power savings and productivity was observed.
    Keywords: thread turning; cutting forces; material removal rate; MRR; robust design; Taguchi method; analysis of variance; ANOVA; orthogonal array; signal-to-noise ratio; cutting speed; depth of cut; infeed angle.
    DOI: 10.1504/IJISE.2020.10030841
  • Simulation modelling for performance optimisation of the skim milk powder production system of a dairy plant   Order a copy of this article
    by Anil Kr. Aggarwal 
    Abstract: The purpose of this paper is to deal with the simulation modelling and performance optimisation for the skim milk powder production system of a dairy plant using genetic algorithm (GA). This analysis is based on Markov birth-death process, the mathematical formulation of the system is carried out to derive first order Chapman-Kolmogorov differential equations by assuming that the failure and repair rate of each subsystem follows exponential distribution. The proposed method is used to compute long run availability using normalising condition, initial boundary conditions and recursive method. It provides the optimum system availability level for different combinations of failure and repair rates parameters of the subsystems of the skim milk powder production system of a dairy plant concerned. The results are presented and discussed with the plant personnel to adopt and practice suitable maintenance policies/strategies to enhance the productivity and quality of skim milk powder production system of the dairy plant.
    Keywords: Markov process; Markov modelling; Chapman-Kolmogorov differential equations; long run availability; performance optimisation; skim milk powder production system.
    DOI: 10.1504/IJISE.2020.10030843
  • Locating warehouses shared by retailers for fast-fashion products considering consumers' waiting cost   Order a copy of this article
    by Zhi-Hua Hu, Jing-Jing Hu 
    Abstract: This study formulates a strategy based on warehouses shared among retailers for fast-fashion products retailing. Consumers can try fashion products' samples at retail stores and the requested products are delivered from a nearby warehouse shared by several retailers. However, the consumers' waiting times decrease service satisfaction and still have the risk that consumers return the delivered products. Aiming at the location problems for the shared warehouses, we consider the waiting cost perceived by consumers and the profit as objectives in a multi-objective mixed-integer linear program. The numerical results demonstrate that the minimisation of waiting cost increases the number of shared warehouses and thus the fixed cost for them, and decrease the profit. The waiting cost is greatly affected by traveling times, delivery cost, fixed cost for shared warehouses, and the waiting cost function of time.
    Keywords: logistics management; fast fashion; warehouse; retailing; waiting cost.
    DOI: 10.1504/IJISE.2019.10030844
  • Biodegradable plastics with natural additives as a replacement for synthetic plastics   Order a copy of this article
    by Amal Elhussieny, Marwa Faisal, Giacomo D'Angelo, Nesma T. Aboulkhair, Nicola M. Everitt, Irene S. Fahim 
    Abstract: A massive outburst in the manufacturing of synthetic plastic has occurred due to its availability, durability and low-cost relative to glass, paper and fabric. In order to combat the plastic pollution phenomenon, it is impossible to eliminate the use of disposable plastic products; however, it could be replaced with an eco-friendly substitute. This study presents a comparison between different composite films with natural reinforcements. The matrices and reinforcements were produced from chitosan extracted from shrimp shells waste and rice straw waste, respectively. Experimental and statistical analysis were performed to define the most desirable filler type and concentration with respect to physical, biological, mechanical and thermal properties. Experimental results showed that the mechanical, thermal, and biological properties of the chitosan (and nano chitosan) films were improved by the addition of 25 wt. % and 35 wt. % of rice straws and nano rice straw fibres.
    Keywords: synthetic polymer; nano science; reinforcements; combinations; food waste; valorisation; natural polymer.
    DOI: 10.1504/IJISE.2020.10028532
  • Production quality improvement for the soft drinks bottling industry through Six Sigma methodology   Order a copy of this article
    by Ismail W.R. Taifa, Ebenezer Dawson Makundi, George S. Mwaluko 
    Abstract: Increase of rejection rate (percentage) in the production process of soft drinks is one of the chronic problems in the soft drinks industry. Over four months, the production rejection rate (PRR) increased up to 12.62%. This resulted in an estimated loss of 93,412,800 Tanzanian Shilling (TZS) at X-Company. Therefore, this study explored how to improve the quality of production in the manufacturing process of the Tanzanian soft drinks industry. The Six Sigma methodology - define-measure-analyse-improve-control (DMAIC) - was employed. DMAIC considers existing products, process and improves the same. An in-depth insight into PRR and speed of acquiring such insight while increasing the problem diversification was successfully performed. Still, soft drinks companies face high PRR. The critical reasons occur during bottle filling and crowning operations. The sigma level was found to be 4.9 with the cost of poor quality being 12.62%. This study achieved a potential annual saving of 280,238,400 TZS.
    Keywords: Six Sigma; Six Sigma methodology; SSM; DPMO; DMAIC; quality improvement; continuous improvement; production rejection rate; PRR; soft drinks; bottling industry; manufacturing rejects.
    DOI: 10.1504/IJISE.2020.10030896
  • A VNS solution and objectives tradeoffs for real-life large-scale vehicle routing problems   Order a copy of this article
    by Yongzhong Wu, Mianmian Huang, Jianjun Yu, Qiran Wang 
    Abstract: With the fast development of urban logistics, real-life vehicle routing problems (VRP) are characterised by their large size and complicated objectives and constraints. In contrast, most research on VRP has been based on classic test cases which are relatively small and have standard objectives. By investigating the case of a real urban security carrier in China, this paper proposes an efficient variable neighbourhood search (VNS) for large-scale VRP with various objectives and constraints, including number of vehicles, total travel time, total travel distance, total waiting time and total late time. The method is used to explore the tradeoffs among different objectives and constraints. It is found that although these objectives and constraints are contradictory by nature, increasing the weighting factor of one does not necessarily undermine (or at least not significantly undermine) the others. Such dynamics in the tradeoffs among different objectives provides users with more flexibility.
    Keywords: vehicle routing problem; VRP; large-scale; variable neighbourhood search; VNS.
    DOI: 10.1504/IJISE.2020.10043244