International Journal of Industrial and Systems Engineering (96 papers in press)

Regular Issues

• Stability Analysis of Asynchronous Switched Positive Systems with Unstable Subsystems  
  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
   
  
• Implementation of Internet of Things (IoT) in Micro, Small and Medium Enterprises: A Case Study  
  by Parikshit Sarulkar, Kumar Srinivasan, Anish Kumar, Vineet Kumar Yadav 
  Abstract: Micro, small, and medium enterprises (MSMEs) play a vital role in India’s economic growth. MSMEs operating in the scrap management sector encounter two main concerns about the transportation cost and scheduling of vehicles. To solve these issues, MSMEs are trying to adopt emerging technologies such as automatic scrap storage, inventory control, and retrieval systems. However, MSMEs are reluctant to implement these technologies due to their pre-assumption of high adoption costs and expected benefits. The present study focused on the effective IoT implementation in vehicle loading to reduce transportation costs and trips in MSMEs. The case study of the scrap managing company has been considered to show the benefits of IoT implementation in MSMEs. The simulation was performed using FlexSim, and the results have confirmed that the IoT implementation can improve vehicle loading by 38% and reduce transportation costs by 38.6%. The outcomes highlight the benefits of IoT deployment in MSMEs.
  Keywords: micro; small; and medium enterprises; MSMEs; scrap management; IoT implementation; transportation; FlexSim simulation.
  DOI: 10.1504/IJISE.2022.10051062
   
  
• Dynamic Futures Margin Setting Method under State Dependence  
  by Wang Hong, Kun Wen, Shouqian Kang 
  Abstract: Margin is not only a basic risk control system for futures trading, but also an important part of the cost of futures trading, and its fundamental position is very important. This paper presents a dynamic margin setting method for futures based on market state, which considers extreme risk control and opportunity cost. In different market conditions, we choose different margin levels to better balance spillover probability and opportunity cost. Using machine learning, we sample the sugar futures traded on the Dalian Commodity Exchange between January 6, 2006, and May 29, 2020. The market is divided into three categories by the hidden Markov model: highly volatile, volatile, and stable. We compare margin level under VaR, CVaR, MMVaR, EWMA and improved EWMA risk standards. Comparative analysis and retrospective test show that the current fixed margin ratio is unreasonable, and the margin level under the single risk criterion cannot balance risk control and opportunity cost well. We recommend that market regulators dynamically adjust margin setting levels according to different market states, thereby luring more investors to invest and boosting the liquidity of the futures market.
  Keywords: dynamic margin level; risk criteria; machine learning; market status.
  DOI: 10.1504/IJISE.2022.10051100
   
  
• Efficient Bayesian optimization of bounded general loss function for robust parameter design  
  by YING CHEN, Mei Han 
  Abstract: Robust parameter design (RPD) has been generally employed to minimise the system quality loss caused by noise perturbation via setting control factors in engineering design. Bayesian optimisation algorithms have received increasing attention for RPD, which includes establishing the Kriging model and developing acquisition functions (AFs). In RPD, the quality loss function method is a common method to calculate the response deviation from a target value. The existing literature mainly focuses on setting the loss function as a quadratic function for easier calculation, while it is not always reasonable due to its unboundedness. In this paper, we propose three efficient Bayesian algorithms for bounded general loss functions for finding the optimal design of control factors based on a Kriging model. We develop a Monte Carlo sampling method to approximate the proposed AFs. Three numerical examples and a rocket injector case are used to demonstrate the effectiveness of the proposed algorithms.
  Keywords: Bayesian optimisation; robust parameter design; RPD; bounded general loss function; acquisition function; Gaussian process model.
  DOI: 10.1504/IJISE.2022.10051366
   
  
• Integration of Modified FMEA Approach with Industry 4.0 Technologies to Improve Reliability of Lean Systems  
  by Karthik Subburaman, Balaji Kuppusamy 
  Abstract: Many organisations are using lean tools with Industry 4.0 technology these days to enhance the sustainability of their lean manufacturing systems. This article contributes by combining a lean tool (modified FMEA) with Industry 4.0 technologies to improve the dependability of lean systems. Under the four lean subsystems of personnel, equipment, materials, and schedules, a redesigned FMEA framework incorporating Industry 4.0 technologies is proposed. From the mapping of lean wastes, Inventory accounts for 39% of total waste, overproduction accounts for 23% of total waste, defects account for 22% of total waste, non-utilised talent accounts for 16% of total waste based on RAV calculation from modified FMEA table. Also based on RPN calculation from the modified FMEA table, Inventory accounts for 45% of total waste, overproduction accounts for 23%, of total waste, defects account for 19% of total waste, non-utilised talent accounts for 13% of total waste.
  Keywords: lean; Industry 4.0; personnel; equipment; materials; schedules.
  DOI: 10.1504/IJISE.2022.10052748
   
  
• In-house part supply logistics optimisation based on the workforce’s ergonomic strain and environmental considerations  
  by Parames Chutima, Chayanee Prakong 
  Abstract: This paper focused on in-house part supply logistics adopted by an automotive manufacturer to make just-in-time deliveries of parts from a supermarket to mixed-model serpentine-shaped assembly lines without shortage. Five objectives are optimised simultaneously, i.e., minimising the total number of tours, minimising the number of tow train drivers, minimising the energy expenditure load discrepancy among tow train drivers, minimising the total inventory kept at the border of the line and minimising the total PM2.5 emission released by a fleet of tow trains. The mathematical model is formulated for the problem. Due to its NP-hard in nature, multi-objective metaheuristics have to be developed for solving practical-sized problem instances. As a result, the non-dominated sorting teaching-learning-based optimisation III (NSTLBO III) which is a hybrid of the non-dominated sorting genetic algorithm III (NSGA III) and teaching-learning-based optimisation (TLBO) is proposed to solve the problem. The results show that NSTLBO III outperforms NSGA III and the multi-objective evolutionary algorithm based on decomposition (MOEA/D) in terms of qualitative, convergence-related and comprehensive metrics.
  Keywords: part feeding; automotive industry; multi-objective optimisation; NSGA III; TLBO.
  DOI: 10.1504/IJISE.2023.10053335
   
  
• Contract Design and Order Decision of Online Retailer's Sharing Surplus Demand with Offline Retailer  
  by Jianjun Yu, Liqian Wang, Yongwu Zhou, Hongkai Fang 
  Abstract: With the gradual slowdown in the growth rate of e-commerce transaction volume, some online retailers choose to cooperate with offline retailers to jointly explore a profit increment path and achieve a new round of profits. In this cooperation mode, the online retailer will share his surplus demand with the offline retailer to complete. This paper designs two kinds of contracts to distribute the cooperative income. In contract 1, the online retailer will return a certain proportion of the cooperative profit to the offline retailer. While in contract 2, the online retailer will provide certain subsidies to the offline retailer according to his order quantity. The results show that contract 1 is dominant when the offline retailer is faced with high demand or slow-volatile demand. However, contract 2 outperforms in the contrary situation. Through sensitivity analysis, it is found that changing the cost or price of the offline retailer can improve the performance of both retailers.
  Keywords: random demand; Stackelberg game; transshipment; revenue sharing contract; ordering decision.
  DOI: 10.1504/IJISE.2022.10053400
   
  
• Integrating noncyclical preventive maintenance scheduling and production planning for a series-parallel production line with stochastic dependence  
  by Ziyad Bahou, Krimi Issam, Abdessamad AitElCadi, Nizar Elhachemi 
  Abstract: This paper investigates the integrated non-cyclical preventive maintenance scheduling and production planning for a series-parallel production line. We consider the stochastic dependence between the components of each subsystem. This problem has not been studied so far in the literature even though it represents a realistic configuration. First, we compute the available production capacity restricted by the stochastic dependence. Then, an integer linear program is used to determine the optimal production plan and preventive maintenance schedule. The results show that ignoring the stochastic dependence effect causes many unexpected consequences and additional production and maintenance costs. This work provides practitioners with a set of managerial insights to develop adequate integrated production and maintenance policies.
  Keywords: production planning; maintenance scheduling; integer programming; series-parallel production; stochastic dependence.
  DOI: 10.1504/IJISE.2022.10053547
   
  
• Ergonomic assessment for work-related musculoskeletal disorders: A case study on office workers in two government organisations in the United Arab Emirates  
  by In-Ju Kim 
  Abstract: This study investigated the pervasiveness of work-related musculoskeletal disorders (WMSDs) amongst office workers from two government organisations (A and B) in the United Arab Emirates. The primary data were collected by self-administrative questionnaire (SAQ), Nordic musculoskeletal survey, and ergonomic assessments with the Rapid Office Strain Assessment (ROSA) checklists. The SAQ survey from organisation A showed that the respondents’ most common pain was the neck (80.00%), whilst organisation B was lower back (78.57%). According to the ROSA results, 86.49% of the respondents in organisation B required ergonomic investigations, whilst 61.76% in organisation A worked under the risk warning regions.
  Keywords: ergonomic assessment; musculoskeletal disorders; MSDs; Rapid Office Strain Assessment; ROSA; work-related musculoskeletal disorders; WMSD; office workers; United Arab Emirates; UAE.
  DOI: 10.1504/IJISE.2022.10053618
   
  
• Product to Process: An Ontology-based approach for product manufacturing process in Flexible Manufacturing System  
  by Imane ZAHRI, Mohamed RHAZZAF, Souhail SEKKAT, Mohammed DOUIMI 
  Abstract: Given the importance and gain of acquiring flexibility and interoperability, the reconfigurability of manufacturing systems remains an active subject of industry research. We propose, in this paper, an ontology-based model for the product’s process for a flexible manufacturing system. This model avoids the technical difficulties related to the product manufacturing design and offers a conversion of the product manufacturing process semantic description to its technical implementation inside the manufacturing system. The ontology is based primarily on the components of the production system and the product life cycle process. We have tested our approach in a flexible cell case study to have the new product manufacturing process using a depth first search-based algorithm applied to the proposed ontology.
  Keywords: product lifecycle management; PLM; new product development; NPD; reconfigurability; ontology; depth first search; DFS; Semantic Web.
  DOI: 10.1504/IJISE.2023.10053656
   
  
• Optimization of reactive precipitation for processing reject brine in Ammonium Perchlorate manufacture  
  by RAMACHANDRA RAO, TIDE P. S, Benny.K George, AJITH PRASAD, JOJO MATHEW 
  Abstract: Ammonium perchlorate (AP) is the most widely used oxidiser for solid rocket propellant formulations. AP manufacture generates a reject brine with 7-8% perchlorates by weight. An optimisation study of reactive precipitation for transforming reject brine into an admixture of AP with ammonium chloride and sodium bicarbonate was conducted at 0.3 m3/batch capacity. The operating conditions play a crucial role in the kinetics of reactive precipitation. Taguchi design and statistical ANOVA were applied to estimate significant operating conditions and their contributions to process performances. The study reveals the potential impact of mixing, type of impeller configuration, and temperature on the process efficiency. A regression model was developed to predict process performances and Taguchi optimum conditions used for getting desirable performances. Subsequently, a multi-response optimiser was applied to find out a set of operating conditions for improving process performance. Experimental validation trials and characterisation were conducted with modified operating parameters and results show considerable improvement in process efficiency.
  Keywords: Taguchi design; ammonium perchlorate; sodium bicarbonate; reactive precipitation; reject brine; optimisation; mixing; regression analysis.
  DOI: 10.1504/IJISE.2022.10053681
   
  
• Experimental modeling and multiobjective optimization of electrochemical discharge peripheral surface grinding process during machining of alumina epoxy nanocomposites  
  by Nandani Singh, Vinod Yadava, Pragya Shandilya 
  Abstract: Machining electrically non-conductive materials is still a very challenging task. So far, electrochemical discharge machining (ECDM) and its configurations, such as drilling-ECDM, TW-ECDM, and milling-ECDM, have been developed for machining such materials. Hence, an in-depth experimental analysis of grinding-ECDM is also required. In the present work, the mathematical models have been formulated using response surface methodology based on Box-Behnken design on the peripheral surface configuration of grinding-ECDM (electrochemical discharge peripheral surface grinding process). Experiments were carried out on alumina-reinforcement epoxy nanocomposites considering supply voltage, pulse on-time, electrolyte concentration, and wheel rotation as input process parameters and MRR and Ra as output performance parameters. The multi-objective optimisation has been done using desirability function analysis (DFA) and grey relational analysis (GRA). The input process parametric conditions obtained from both optimisation methods are different. It has been found that DFA shows slightly better results than GRA for both MRR and Ra.
  Keywords: desirability function analysis; DFA; ECDM; ECDPSG; Grey relational analysis; GRA; grinding; multi-objective optimisation; polymer nanocomposite; PSN.
  DOI: 10.1504/IJISE.2023.10053851
   
  
• An empirical investigation of Lean Manufacturing dimensions through Structural equation modeling  
  by Amjad Khalili 
  Abstract: This paper aims to recognize Lean Manufacturing (LM) two dimensions namely soft (SLM) and hard lean (HLM). It empirically examine the linkages between these perspectives and contributes to operations management literature by focusing on the aspects managers attempt to embrace in their industries. It censoriously examines these practices as scarce research discussed these together. Besides, the importance of their adoption is reflected and relevant key factors introduced. To achieve this, a conceptual model is established and its applicability explored. The postulated hypothesis is further tested through data gathered from Palestinian industries through the developed questionnaire and both SPSS 23 and AMOS 23 are considered for analysis. Findings imply that both can be found together and their linkages is supported. Manufacturers may apply these models to establish a better implementation environment in their manufacturing facilities using the appropriate integrated LM frameworks.
  Keywords: Soft lean; hard lean; importance; model; applicability; AMOS.
  DOI: 10.1504/IJISE.2023.10054049
   
  
• Advanced delay-time analysis applied to carbon black powder production  
  by Marc Fischer, Bryan Jones 
  Abstract: Delay time models (DTM) for series systems divide the failure of a system into the appearance of defects and the delay until the breakdown. During this work, we developed four new DTM whose main novelty consists of considering cheaper online inspections preceding offline inspections. Our numerically tested models were applied to a previously published study about a carbon black factory. After the improvement of problematic assumptions, the optimal inspection period turns out to be considerably larger than in the previous study, which emphasises the need to flexibly develop new delay-time models when facing unusual situations and to avoid a reliance on black boxes. The correct handling of environmental consequences has a tremendous impact upon the optimal maintenance decision.
  Keywords: Delay Time; Poisson Process; Maintenance; Monte-Carlo.
  DOI: 10.1504/IJISE.2023.10054146
   
  
• Elaboration of Water Distribution Schedules in Periods of Scarcity  
  by Tatiana Balbi Fraga, Aldênia Karla Barrêto Candido, Marcos Henrique, Abdeladhim Tahimi 
  Abstract: Scarcity of treated water is a global problem that directly impacts the quality of life and, therefore, brings to light the need for more careful management of water resources in locations that are affected. Although there is a vast literature on the problem of design and operation of treated water distribution networks, few studies consider the issue of scarcity. In the present paper, we carry out a study on the real water distribution problem of a city located in Northeastern Brazil. In this study, we conceptually and mathematically model the problem addressed as a new specific water distribution optimisation problem, and implement the model developed using LINGO software from LINDO systems. We conclude the study showing that the developed solver is a practical, effective and efficient tool, which can be easily used by a suitably qualified employee.
  Keywords: mathematical modelling; water distribution schedules; water distribution system; WDS; water scarcity; LINGO.
  DOI: 10.1504/IJISE.2023.10054305
   
  
• QUALITY ASSURANCE USING ACCELERATED LIFE TESTING VIA REBATE WARRANTY  
  by Showkat Ahmad Lone, Intekhab Alam, Sabir Ali Siddiqui, Ritu Rathee 
  Abstract: Accelerated life testing (ALT) has now become the primary method for rapidly assessing product reliability. Designing highly effective test models is a vital step in ensuring that ALT can properly, quickly, and economically assess product reliability. These tests subject the sample to high levels of stress. Then, based on the stress-life relationship, the failure data can be extrapolated from a sample at a high-stress level to a normal level to calculate product life at usual operating conditions. The study is an advanced proposal to analyse ALT schemes for the quality improvement and reliability of modern products. The problem is investigated using constant stress, assuming that the unit lifetimes follow the power-function distribution. Furthermore, as a procedure that employs ALT to predict the cost of age replacement of goods covered by a warranty agreement. A mathematical example is also used to demonstrate theoretical findings. The result will prove an asset for marketing providers in estimating the various costs associated with the product under the warranty policy. Hence, it can help manufacturers to increase the reliability/quality of their products to achieve consumer satisfaction.
  Keywords: product life acceleration; age-replacement warranty; power-function model; simulation analysis; accelerated life testing; ALT.
  DOI: 10.1504/IJISE.2023.10054347
   
  
• Just in Time and Supply Chain Finance: A Hierarchal Model Development  
  by Imran Zaman, Md. Ramjan Ali, Sharfuddin Ahmed Khan 
  Abstract: This study aims to investigate whether or not just in time (JIT) and supply chain finance (SCF) have a synergistic impact on overall organization performance. The purpose of this study is to help address this knowledge gap and shed light on the role that JIT tools plays in optimizing the benefits that SCF offers to an organization as a whole. Interpretive structural modeling (ISM) and Decision making trial and evaluation laboratory (DEMATEL) has been used to explore relationship, contextual link and hierarchical interpretation between JIT and SCF characteristics. Results shows that, the variables with the highest rankings in ISM and DEMATEL are employee attitude, embeddedness of continuity practice, and changing level and position of inventory maintained by businesses. Integration of JIT and SCF will help organizations to increase in revenues, a reduction in waste, an improvement in cash flow, and a reduction in supply chain hazards.
  Keywords: Supply chain finance; Just-in-time; Organizational performance; Interpretive Structural Modeling; Decision Making Trail and Evaluation Laboratory; FMCG industry.
  DOI: 10.1504/IJISE.2023.10054392
   
  
• Profit Analysis of Utensils Manufacturing System of Steel Industry  
  by Sapna Saini, Jitender Kumar, M.S. Kadyan 
  Abstract: The objective of the present study is to deal with the profit analysis of utensils manufacturing system of steel industry which has six subsystems:
  Keywords: profit analysis; steel industry; availability analysis; supplementary variable technique; utensils manufacturing system.
  DOI: 10.1504/IJISE.2022.10054606
   
  
• Value chain analysis of Biodiesel production from animal fat: A case of Botswana  
  by Nosi K. P. Moakofi, Jerekias Gandure, Venkata P. Kommula 
  Abstract: Botswana as a developing country, is currently investing in biodiesel production, however, no data on biodiesel value chain characterisation is available to establish viability and sustainability of biodiesel production. This study characterised the value chain of animal fat biodiesel in respect of feedstock supply, production, and end use. The purpose of the study was to assess potential of animal fat feedstock to sustain envisaged biodiesel industry in Botswana. Methods used in the study include questionnaire surveys and interviews. Key findings of the study indicate that animal fat-based biodiesel value chain is unstructured, stakeholders are disintegrated and unregulated, and the country produces enough fat to yield tallow potential to produce 205,345 litres of biodiesel per month. The findings indicate the need for regulating and promoting animal fat-based biodiesel value chain with policies and establishment of entities to integrate value chain stakeholders as well as exploring all opportunities within the value chain.
  Keywords: value chain; biodiesel; animal fat; production; Botswana.
  DOI: 10.1504/IJISE.2023.10054811
   
  
• Reliability Assessment of Dragline’s subsystem using Dynamic Bayesian Network  
  by Deepak Kumar, Debasis Jana, Suprakash Gupta, Pawan Kumar Yadav 
  Abstract: Draglines are very complex in design and consist of hundreds of components. Ensuring the high reliability of a dragline is essential for the economic sustainability of a surface mining project. This study proposes a methodology for the reliability assessment of the dragline’s subsystem using the dynamic Bayesian network (DBN). The reliability of the dragging subsystem highly depends on the reliability of the drag brake, drag socket, and power failure. The dragging subsystem reliability is 84.29% at 1 hr. of machine operation. This study provides useful data for dragline maintenance planning and a reliability design.
  Keywords: dynamic Bayesian network; DBN; reliability; dragline; opencast mine; mining machine.
  DOI: 10.1504/IJISE.2023.10054814
   
  
• A FORECAST MODEL FOR WORKERS’ PERFORMANCE IN MASS CUSTOMIZED PRODUCTION  
  by Le Song Thanh Quynh, June Ho, Thi Kim Hue Trinh 
  Abstract: There has been a shift to mass customisation production for most of the manufacturing systems in recent decades. This leads to the need of predicting workers’ performance for task assignments for all the main steps in manufacturing. However, the literature review shows that while most scholars pay more attention to the investigation of factors impacting worker performance; how these factors can be used to support decision making in task allocation is still in its infancy. This paper will propose a new method for determining the workers’ performance by devising a rule-based system for the assembly manufacturing line. The application of previous experience, scientific knowledge, and historical data will increase the accuracy of the productivity and quality predictions.
  Keywords: workers’ performance; rule-based systems; decision tree; decision support technique.
  DOI: 10.1504/IJISE.2023.10055318
   
  
• Identifying The Implementation of Neural Network Approaches in Peer-to-Peer Lending Research: A Bibliometric Based Thematic Approach  
  by Alok Kumar Sharma, Li-Hua Li, Bhartrihari Pandiya, Ashish Dwivedi 
  Abstract: Peer-to-peer (P2P) lending market has exploded in popularity since the last decade. The proliferation of data has given opportunities to prediction models, such as neural network (NN), to analyse and forecast risk assessment. The objective of this research is to explore the intersection of NN models in P2P lending and identify future trends for NN in this field. A systematic literature review (SLR) was conducted using the PRISMA model and bibliometric analysis, which included network and thematic investigation approaches for the NN in P2P lending research published over the last decade. The study analysed the key trends in select research domains, identifying four themes: predictive analysis, financial risk, convolutional neural networks, and P2P networks. The research also identified citation networks with four clusters: investor behaviour, borrower behaviour, classification models for credit scoring, and borrower default prediction. Further, analysis was performed on the most cited documents, emphasising the research methods, models, and datasets used in the articles.
  Keywords: neural networks; decision analytics; bibliometric analysis; P2P lending; credit risk assessment.
  DOI: 10.1504/IJISE.2023.10055561
   
  
• Decentralized control of heterogeneous interconnected systems with asynchronous sampling  
  by Shiqiang Zhang, Zidong Liu, Dongya Zhao 
  Abstract: In this paper, the asynchronous sampling control problem for linear heterogeneous interconnected systems has been investigated. By utilising the Lyapunov-Krasovskii approach and robust control theory, some sufficient conditions based on linear matrix inequalities (LMIs) are presented such that the stability and performance of closed-loop system can be guaranteed. On the basis of these conditions, a novel decentralised algorithm based on relaxation and successive distributed decomposition (RSDD) method is proposed to calculate the state feedback gains over the systems, which significantly reduces the computational complexity. The effectiveness of the proposed schemes are verified via some simulations.
  Keywords: heterogeneous interconnected systems; asynchronous sampling; computational complexity.
  DOI: 10.1504/IJISE.2023.10055602
   
  
• Determinants of Blockchain- Machine Learning Adoption in Additive Manufacturing  
  by Swati Narwane, Irfan Siddavatam, Mahesh Kavre 
  Abstract: This work concentrates on determining, inspecting, as well as ranking the critical barriers and alternatives to help the adoption of BC-ML practices in additive manufacturing (ADM). AHP-VIKOR methodology was applied to examine 20 identified barriers within the BC-ML adoption in ADM. The findings of the study reveal the rankings of the significant barriers as well as alternatives aimed at the trouble-free adoption of BC-ML practices in the ADM industry. Higher build time and complicated design process of blockchain-based platforms emerge as the most critical barriers, with a higher value of weights by using the AHP approach. The outcome of the alternative evaluation shows that the vat polymerisation process ranks at the topmost position. The findings of this study can be useful to practitioners and policymakers to develop proper understanding, alleviation approaches, and make well-informed decisions.
  Keywords: machine learning; additive manufacturing; ADM; blockchain; vlekriterijumsko kompromisno rangiranje; VIKOR; analytical hierarchy process; AHP; implementation barriers.
  DOI: 10.1504/IJISE.2023.10055740
   
  
• Decentralized sliding mode control for a class of nonlinear interconnected systems with unstable internal dynamic  
  by Kai Sun, Jiehua Feng, Dongya Zhao 
  Abstract: In this paper, the problem of decentralized sliding mode control for nonlinear interconnected systems with unstable internal dynamic is studied. For each subsystem whose internal dynamic is unstable and can be linearized, a sliding surface composed of corresponding subsystem state variables is designed and the stability of sliding mode dynamic is analyzed. Under a reachability condition, a decentralized sliding mode control is designed to force the interconnected system states to the sliding surface in finite time and maintain a sliding motion thereafter. The proposed method is proved effective through a simulation example of double translational oscillator with rotational actuator (TORA).
  Keywords: Nonlinear Interconnected Systems; Unstable Internal Dynamic; Decentralized Sliding Mode Control.
  DOI: 10.1504/IJISE.2023.10056415
   
  
• A logistics planning model for Dual Tank-containers Combined-transport Network  
  by Ruyi Fan, Junmin Yi 
  Abstract: A combined-transport network model with dual tank-containers of IBC and ISO Tank by both trucking and waterborne is created to optimise the route planning and resource allocation of the dual tank-containers, which cares the cost of refilling liquid from Tank to IBC, refilling facility cost and inventory limit on the water-land transfer nodes. Also, the transport service level of the model is monitored by proportional transportation fulfilment and vehicle loading rate. The instance results and sensitivity analysis show that the model has optimal transportation cost, more proportional and robust network planning. Thus, it is a good reference for managers to design a more suitable dual tank-container combined-transport network planning according to the real logistics situation and actual needs.
  Keywords: transport; tank-container; logistics planning; sensitivity analysis.
  DOI: 10.1504/IJISE.2023.10056638
   
  
• Six Sigma methodology implementation for minimising yarn breakages in the apparel industry  
  by Seleman Kalinga Hussein, Ismail W. R. Taifa 
  Abstract: This research applied the Six Sigma methodology (SSM), mainly the define-measure-analyse-improve-control (DMAIC) approach to minimise the yarn breakages in the weaving loom during the woven fabric manufacturing. The product rejects were 512,000 metres, and the production quantities were 13,273,512 metres of fabrics. The calculated sigma level was 4.84, and the cost of poor quality (COPQ) was 14.36%. After the improving and control phases, the company implemented the solutions for four months, thus leading to a COPQ of 7.18%. The potential solutions include the effective performance of the weaving preparatory process, analysis of material parameters and yarn unevenness testing, and improving the adequate weaving loom’s atmospheric condition. Other recommendations include regular machine maintenance, installation of stretch control devices on warping machines and tension control device (tensiometer) on a sizing machine, proper weaving machine setting and providing technical skills to operators and quality control staff about weaving production and quality management techniques.
  Keywords: Six Sigma; SS; Six Sigma methodology; SSM; DPMO; DMAIC; cost of poor quality; COPQ; yarn breakage minimisation; weaving loom.
  DOI: 10.1504/IJISE.2023.10056743
   
  
• Failure Function Matrix for Interconnected Equipment Failure Analysis  
  by Niguss Haregot Hatsey, Amanuel Amare Gebrekidan 
  Abstract: Failure is an inevitable phenomenon, therefore, it is essential to develop state-of-the-art failure analysis tools that enables to deal with it. Even though there are several failure analysis tools, they lack to analyse the failure interdependence in complex system. In this study, a new failure function matrix (FFM) is proposed to analyse the cause, effect, and solution of an equipment by considering both the internal and external interdependencies. An empirical study is conducted on electrical infrastructure failure of Raya Azebo Ground water, Ethiopia. The study revealed that there is failure interdependency among devices interconnected in a complex system. The FFM can be applied to analyse failure of various infrastructures in a system level than a specific equipment. This study contributes a novel FFM tool that enables to analyse comprehensively overall failure function (cause, effect, and solution) and to analyse failure from end-to-end in a system level by considering the failure interdependency among interconnected equipment.
  Keywords: equipment failure; failure analysis; interconnected equipment; complex system.
  DOI: 10.1504/IJISE.2023.10057014
   
  
• Electric Two-Wheelers: The Future of Short Hauls  
  by Samarth Singh 
  Abstract: This article looks at the elements which impacts individuals' decisions to acquire electric two-wheelers. It also evaluates the many aspects of electric two-wheelers that customers like before making a purchase. An online poll was used to gather primary data. A total of 204 answers were collected and regression analysis was performed using SPSS version 22.0. This article shows that the general public is willing to switch to electronic vehicles as a daily commute if their value increases. India, as a potential market, offers large markets for electronic vehicles to cater to clients ready to use electric two-wheelers as a daily commute, resulting in a win-win situation for all parties involved. This study is unique as it assesses customers' impressions of electric two-wheelers as a daily commute, which is backed up by robust empirical evidence acquired through primary data collection and the new road ahead in the coming time.
  Keywords: electric two-wheelers; customer perception; features; buying action/behaviour; regression.
  DOI: 10.1504/IJISE.2023.10057213
   
  
• An Empirical Analysis of Forecasting Methods for Trauma Injuries in Rural Areas  
  by Alakshendra Joshi, Eduardo Pérez, Francis Mendez 
  Abstract: Trauma is an essential aspect that must be considered by governing bodies when providing and expanding healthcare services across their jurisdiction. This study focuses on analyzing and forecasting physical trauma sustained from accidents, in environments both personal and work related, pertaining to individual injuries but not excluding the scope of large-scale natural disasters. The goal of the study is to better understand the limitations faced by the existing trauma healthcare infrastructure by forecasting the expected number of people requiring the services of trauma facilities in rural areas. Five types of forecasting methods were analyzed to determine the best option to utilize for forecasting for individual data sets. Out of these models, ARIMA proved to be the best performing method for a significant majority of the individual data sets.
  Keywords: Trauma; Time series forecasting; Patients; Facilities; ARIMA.
  DOI: 10.1504/IJISE.2023.10057285
   
  
• Evaluating Impacts of Anchorages Reprovisioning Scheme on Mega Port Operations: Simulation Approach  
  by Youhong Liao, Sifan Tu, Yongzhong Wu 
  Abstract: Anchorages play important parts in both vessels waiting for berth and cargo handling at sea. As a kind of public marine resource, anchorages often need to be reallocated for different reasons including land reclamation. The usage of the anchorage area is considered to be a complex queuing system. Therefore, building a simulation model to evaluate the impacts of the reallocated anchorages is a relatively practicable and accurate method. This article explores the impacts of the reduced anchorages in Hong Kong’s Central Water due to land reclamation project, by establishing a simulation model. The analysis of the model helps to evaluate the impacts and suggest on the anchorage re-provisioning scheme. Relative simulation models and methods provide a scientific basis for the analysis, design, and planning of anchorages in other ports.
  Keywords: simulation; port operations; anchorage capacity; service management; queuing system.
  DOI: 10.1504/IJISE.2023.10057877
   
  
• Design and Experimental Validation of Normal Terminal Sliding Mode Control for Level Tank System  
  by Ajit Laware, Sanjay Joshi, Vitthal Bandal, Dhananjay Talange 
  Abstract: The paper explores design of a normal terminal sliding mode controller (normal TSMC) for nonlinear uncertain laboratory level tank system. The reachability condition of closed-loop system has been deduced from direct Lyapunov candidate function. The proposed design method has been compared with proportional, integral and derivative (PID) controller and typical sliding mode control (SMC). Normal TSMC and classical SMC are verified by using simulation as well as real-time experimentation while PID controller has been validated via experimental tests. The simulation and experimental result investigates that normal TSMC algorithm is superior than PID and SMC strategies for estimated plant parameters, switching the set-point from one level to other and internal, and external disturbances. It explores the better improvement in time-domain specifications such as response speed, settling time, overshoot in percentage, rise time and error performance indices.
  Keywords: level tank system; normal terminal sliding mode control; proportional; integral and derivative controller; real-time experimentation.
  DOI: 10.1504/IJISE.2023.10058295
   
  
• Selection of sustainable materials for additive manufacturing processes: A hybrid AHP-DEMATEL approach  
  by Ashish Dwivedi, Siddharth Parihar, Rajeev Agrawal, Fuli Zhou, Saurabh Pratap 
  Abstract: Additive manufacturing (AM) is vital to medical, aerospace, food, and automotive manufacture. AM makes complex products. Sustainable materials that enable cleaner manufacturing and reuse are essential in this fast-changing globalised environment. Polymers and nickel superalloys are employed in AM to meet these needs. This study uses an analytical hierarchy process (AHP) and decision-making trial evaluation and laboratory methodology (DEMATEL) to evaluate polymer laser sintering (PLS) and nickel-based superalloy for different AM procedures. DEMATEL's findings will show a link between PLS criteria and Nickel-based superalloys. This study conducts two case studies. AHP and DEMATEL techniques weight material cost as the most essential parameter for both case studies. In the PLS case study, polycarbonate is the most sustainable material, and based on weightage, INCONEL 718 is the most sustainable nickel-based superalloy. Two case studies will demonstrate criterion interdependence and score the material. The study's findings can help AM technology material selection.
  Keywords: additive manufacturing; polymer laser sintering; PLS; Nickel Superalloys; AHP; DEMATEL.
  DOI: 10.1504/IJISE.2023.10058427
   
  
• Shift work disorders in electric control center operators: Assessment, prevalence, and proposal of a new rotating shift duty system for the workability improvement  
  by In-Ju Kim 
  Abstract: This study assessed the workability effects and identified factors that reduce workability among rotating shift duty operators in electricity distribution control centres of the United Arab Emirates (UAE). Fifty-two operators from two control centres participated in the present study. Qualitative data were amassed by reviewing the database and collecting cross-sectional surveys from the centres' operators. The surveys were designed to obtain sociodemographic, health, and lifestyle information and contained work ability index (WAI) scores and survey feedback through open-ended questions. Results were assessed statistically using Pearson chi-square and cross-tab analyses. This study identified that a significant part of the staff workability deterioration was associated with rotating shift duty due to the critical impact on operators' health and mental resources. Based on the findings, several recommendations, including a new rotating shift duty system, were suggested to reduce the current system's adverse safety and health effect and improve operators' workability.
  Keywords: control room operators; safety and health; shift work duty; sleep disturbance; workability.
  DOI: 10.1504/IJISE.2023.10058428
   
  
• Integrated quality and decision-making approaches-based framework for risk analysis  
  by Dilbagh Panchal 
  Abstract: The aim of the proposed integrated framework is to study and analyse the risk issues of electrostatic precipitator (ESP) unit in a thermal power industry. Under the proposed framework, a well-known quality tool namely failure mode and effect analysis (FMEA) has been implemented for listing the detailed qualitative information related to the considered unit. Failure causes associated with various components of the unit are prioritised using fuzzy combinative distance-based assessment (FCODAS) decision-making approach within FMEA approach. Further, to evaluate the consistency of the proposed framework a well-established fuzzy-technique for order of preference by similarity to ideal solution (TOPSIS) approach was also applied and the ranking results are compared. From the ranking results it was found that failure cause-overloading (IBU) of insulating bush; is the most critical failure cause which may result in sudden failure in the unit operation. Sensitivity analysis has been also carried for checking the robustness of the proposed integrated framework. The results have been supplied to the maintenance manager of the considered unit for developing the quality maintenance schedule for the considered unit.
  Keywords: electrostatic precipitator; quality; failure mode and effect analysis; FMEA; risk; fuzzy; FCODAS; TOPSIS.
  DOI: 10.1504/IJISE.2023.10058495
   
  
• Impacts of Logistics Models and Freight Subsidy on the Possibility of Consumers Using Cross-Border E-Commerce platform  
  by Yongzhong Wu, Zhi Jie Zhu, Yan Li 
  Abstract: The cross-border e-commerce platform led by Shopee has adopted two logistics models, overseas warehouse and cross-border direct mail, and implemented a freight subsidy policy to increase users’ purchase intention, but the large amount of freight subsidy has also caused the company to lose money year after year. Based on the above background, this paper explores the impact of logistics models and freight subsidies on the demand of bilateral cross-border e-merchants by using Shopee, a representative company of China-Southeast Asia cross-border e-merchants, as the research object. On this basis, the model is used to calculate user demand in two logistics modes and further compare the probability of user purchase choice in two typical regions under different logistics modes. Finally, the changes of e-commerce demand under the platform as a whole and different logistics modes are explored when the freight subsidy strength is retreated through the introduction of freight subsidy strength.
  Keywords: Shopee; binary logit model; logistics model; freight subsidy.
  DOI: 10.1504/IJISE.2023.10058542
   
  
• A Multi-Objective Hitch Avoidance Algorithm Using NSGA- II  
  by Monika Dhiman, Pratima Manhas 
  Abstract: One of the core issues and a key component of research on mobile robot motion planning, particularly in environments with complexity is the model of motion in the second order. Based on the model, this investigation suggests an advanced strategy for educating artificial authenticate to navigate around hitch in zestful settings. First, a mathematical model is created that takes environmental information into account, conditions like the path taken by a mobile robot as well as the velocity and orientation of obstructions. Second, a brand-new non-dominated sorting genetic algorithm (NSGA) is used to look for a solution to the mathematical model's multi-objective optimisation issue. Finally, the mobile robot can safely achieve the target by modifying its speed and direction to avoid hitches in real time. The facsimile experiment shows that the method transcends of artificial potential field (APF) algorithm and the genetic technique which avoids the hitch in the context of artificial.
  Keywords: artificial potential field; APF; non-dominated sorting genetic algorithm; NSGA.
  DOI: 10.1504/IJISE.2023.10058905
   
  
• Multi-objective collaborative slot secondary allocation model with curfew restriction  
  by Kejia Chen, Xiaoqing Guo, Haiyan Wang 
  Abstract: The paper explores the flight recovery problem of flight delay and violation of airport curfew due to the decline of airport capacity under the collaborative decision making. A multi-objective collaborative slot secondary allocation model is proposed to minimise the total delay cost of airlines and the total delay time of passengers. Three multi-objective decision-making (MODM) techniques are introduced, and the displaced ideal solution (DIS) method is used to select the optimal solution technique. The results show that the weighting method (WM) can generate high-quality solutions in the test data set. Finally, combined with the delayed flight data of an airport, LINGO software is used to solve the model, the sensitivity and the complexity is analysed. The results show that the collaborative scheduling strategy proposed in this paper can provide airlines with scientific and reasonable slot secondary allocation scheme under the condition of limited airport capacity.
  Keywords: flight recovery; airport curfew; slot secondary allocation; multi-objective programming.
  DOI: 10.1504/IJISE.2022.10058909
   
  
• Application of Machine Learning algorithms in Supply Chain Disruption Management: An Indian MSME Perspective  
  by Arun Thomas, Vinay Panicker, Midhun R. P 
  Abstract: Recently, research on supply chain risk have gained more attention since disruptive events occur more frequently. Therefore, companies focus on identifying the probability of the occurrence of the disruptive event before its occurrence to develop resilient strategies. In this research, the dearth of applications of predictive modelling in risk management, particularly for the MSME sector companies has been addressed. A seasoning and flavours manufacturing company located in the southern part of India, was selected for the study. A prediction framework was developed for the prior identification of order delivery delay. A dataset having almost the same features was selected from a public repository and used for analysis. Based on the prediction priorities of the company, the average recall score is selected to evaluated the developed model. A web-based application to identify the delivery delay of orders was also developed.
  Keywords: supply chain disruption; machine learning; prediction model; MSME; delivery delay.
  DOI: 10.1504/IJISE.2023.10058976
   
  
• Analysis of Non-Markovian Queuing system in the Productivity Control of Cotton Industry under disaster  
  by S. Jeyakumar, Logapriya B 
  Abstract: Queueing system with optional second service under disaster is focused in this article to study its behaviour, in which every customer receives the necessary service and only the customers who specifically request the second optional service receives it. The server may take a vacation based on a Bernoulli schedule after every service completion. Finally, when a disaster affects the system, the server starts the repair period, which causes all customers who are waiting and being served to leave the system. We obtain the probability generating function of a queue size distribution with a minimal set of performance metrics using the supplementary variable technique. Some rate arguments and cost model analysis are derived. Additionally, a numerical illustration is given to study the impact of parameters in the model.
  Keywords: supplementary variable technique; second optional service; disaster; Bernoulli vacation schedule.
  DOI: 10.1504/IJISE.2023.10058979
   
  
• A Retailer's Inventory Model for Deteriorating Items under Power Pattern Demand with Shortages Partially Backlogged in both Crisp and Fuzzy Environments  
  by Sourav Kumar Patra, Susanta Kumar Paikray, Rudra Mohan Tripathy 
  Abstract: An inventory predicament can be resolved with numerous techniques, starting from the trial-and-error manner of mathematical and simulation methods. Mathematical methods always serve as powerful tools for minimising total inventory costs. In this paper, we have considered a retailer's inventory problem in order to determine an optimal strategy that minimises the total inventory cost under various constraints. Here, the constraints include constant deterioration, power-pattern demand, permissible shortages, partial backlog, different inventory costs, and inherent imprecision of various expenses concerning the current scenario. Subsequently, we develop the mathematical model of the problem together with its solving policy in a crisp as well as fuzzy environments. Moreover, we provide several numerical illustrations to validate our findings. Finally, we present several managerial insights for inventory managers based on the sensitivity analysis of associated parameters.
  Keywords: inventory optimisation; power demand; deterioration; partial backlogging; triangular fuzzy numbers; signed distance method.
  DOI: 10.1504/IJISE.2023.10059117
   
  
• A conceptual human safety system in an industrial shared workspace with a collaborative robot  
  by Marcos Vido, Athos Pacchini 
  Abstract: By working side-by-side with humans in a production environment, collaborative robots (cobots) can be helpful and versatile and can efficiently support activities in modern factories. A review of the extant literature identified an opportunity to build user-friendly human-robot interfaces and confirmed the need to enhance the perceptions of human safety conditions and requirements during interactions with cobots when performing manufacturing tasks. Therefore, this study seeks to deepen the knowledge regarding the use of cobots, based on introducing novel safety system architecture for human-robot collaboration in a shared workspace. The degree of collaboration is investigated, focusing on the safety requirements when human operators perform tasks involving cooperation between humans and cobots in a combined workstation. As a result, this study extends the previous literature by proposing a conceptual safety system architecture that is especially useful for covering safety requirements during the design stage of a collaborative workstation so as to minimise safety risks to humans, resulting in a dynamic safety framework that allows for the use of advanced robotics in an Industry 4.0 environment.
  Keywords: collaborative robot; safety; human-robot collaboration; HRC; cyber-physical systems; CPSs; Industry 4.0.
  DOI: 10.1504/IJISE.2023.10059230
   
  
• Process Capability Indices Cp and Cpk under AR (2) Process  
  by Mahesh Deshpande, Vikas Ghute 
  Abstract: Process capability indices are widely used by quality practitioners to quantify the capability of given manufacturing process. The process capability indices Cp and Cpk are based on the assumptions of independence and normality of the process characteristic. Many authors have reported that if we ignore the autocorrelation present in the process characteristics lead to wrong decisions. In this paper, the effect of the autocorrelation on the capability indices Cp and Cpk is discussed. The second order autoregressive process AR (2) is considered to model the data from an autocorrelated process. To reduce the effect of autocorrelation on the indices and the skip and mixed sampling techniques are implemented to form rational subgroups in the design of these indices. Results based on simulation study confirm that both the techniques improve estimate of capability indices Cp and Cpk significantly.
  Keywords: process capability index; subgroup; autoregressive process; s-skip and mixed sampling.
  DOI: 10.1504/IJISE.2023.10059234
   
  
• Customer Satisfaction Optimization in a Dynamic Closed-Loop Supply Chain under uncertainty  
  by Hanieh Shambayati, Mohsen Shafiei Nikabadi, Mohammad Rahmanimanesh 
  Abstract: Optimising the management of the closed-loop supply chain (CLSC) has attracted considerable attention over the past few years. But most researches in this area have only considered the cost and profit functions. In this research, the optimisation of Multi-product CLSC considering customer satisfaction with dimensions such as quality, service level, lead time, and environmental pollution along with the profit function in different periods is considered. The uncertainty of demand in the form of grey numbers is considered. To optimise this NP-hard problem, a multi-objective meta-heuristic pareto-based enhanced firefly algorithm was used. The purpose of the proposed model is to determine the optimal production quantities of each product and finding the location of the warehouse at each stage and period in the CLSC. Finally, for the validity and analysis of the model, a numerical example has been considered.
  Keywords: closed-loop supply chain; CLSC; customer satisfaction; optimisation; uncertainty; grey numbers; enhanced firefly algorithm.
  DOI: 10.1504/IJISE.2023.10059290
   
  
• Vehicle Routing Decision-Support System Development using Integer Programming and Heuristics: A Model-Driven Structured Approach  
  by Aneta Jajou, Ahmed Azab, Sally Kassem 
  Abstract: In this article, a model-driven structured approach is adopted to develop a decision support system for the capacitated vehicle routing problem. A repository of artefacts is developed through system initiation, analysis, design, and implementation. Data about the problem is gathered, and existing procedures are analysed and improved using key stakeholders’ knowledge to maintain continuous communication throughout the stages with involved parties. The DSS adopts mathematical programming and a heuristic to obtain exact and good solutions. The nearest neighbourhood heuristic is employed to solve large instances. IDEF0 and a problem statement are employed for system initiation. A cause-effect analysis is conducted for problem analysis. Use-case diagrams and narratives are used for requirements analysis. Logical and physical data flow diagrams are developed for system design. The system is implemented using Excel internal VBA language and the Application Programming Interfaces for Frontline Solver and Google Maps. Fico Xpress is used for exact solutions.
  Keywords: model-driven software engineering; decision support system; DSS; vehicle routing problem; VRP; logical design; system construction.
  DOI: 10.1504/IJISE.2023.10059413
   
  
• Machine learning based conflict-free trajectory generation  
  by Yungxian HAN 
  Abstract: With the rapid development of the aviation industry, air traffic flow is showing a rapid growth trend, and the mutual influence and interference between aircraft in the airspace are also increasing. In order to ensure the safe and orderly operation of air traffic flow, it is urgent to propose efficient conflict-free trajectory generation methods. The development of artificial intelligence technology provides a new way for the design of conflict-free trajectory generation algorithms. As a consequence, machine learning can be applied to conflict-free trajectory generation. Intelligent agents learn autonomously in their interactions with the environment, thus possessing the ability to make autonomous decisions. Simulation experiments in different scenarios have shown that the algorithm proposed is effective.
  Keywords: machine learning; air traffic control; conflict management; trajectory planning.
  DOI: 10.1504/IJISE.2023.10059447
   
  
• A Game-Theoretic Approach for Analyzing a Competition Between Electric and Hydrogen-Based Vehicles in a Supply Chain to Reduce Carbon Emission Under Government Strategies  
  by Mahnaz Naghsh Nilchi, Morteza Rasti-Barzoki 
  Abstract: In recent decades, climate change and air pollution have become major global challenges due to population growth and increased fossil fuel use. Electric and hydrogen vehicles have emerged as sustainable alternatives, reducing greenhouse gas emissions and improving air quality. Both offer co-benefits in reducing air pollutants from common emission sources. However, the study shows that despite higher demand for electric cars, hydrogen car manufacturers still yield greater profits. The preference for consumers and governments is more towards electric cars due to higher demand and better environmental impact. Nevertheless, the hydrogen car market remains profitable for manufacturers. Governments may play a role through tax and subsidy policies to incentivise consumers towards more sustainable choices, contributing to environmental protection and public health preservation.
  Keywords: electric car; hydrogen car; government policy; pollution pricing; sustainability; game theory.
  DOI: 10.1504/IJISE.2023.10059595
   
  
• Clustering evaluation of energy efficiency in the inlet pump room based on BP-DEMATEL and improved CRITIC method  
  by Yi Guo, Miao Zhou, Jun Xie, Wei Zhong Huang, Pan Geng 
  Abstract: As China issues to develop implementation plans for reaching carbon peak and carbon neutrality in critical regions, the sewage treatment industry has to push energy and industrial structure transformation and upgrading. Whether the inlet pump room can perform effectively and energy-saving will directly impact the economic operation of the whole enterprise. This paper seeks to build a complete energy efficiency assessment model for the pump room. Firstly, the calculation and standard range of five relevant indicators are carried out. Secondly, the indicator weight algorithm of BP-DEMATEL and improved CRITIC technique is proposed, and the linear coupling weighting is adopted according to minimal discernment information. Alternatively, an OPTICS clustering approach based on Bayes optimisation is also presented to obtain the range for four operating conditions. Finally, empirical research is carried out on the case of the pump room in Shanghai. The researched model may greatly increase the assessment performance, giving the scientific reference value for the optimisation of the pump room renovation.
  Keywords: BP-DEMATEL; improved CRITIC method; Bayesian optimisation; OPTICS clustering; energy efficiency assessment.
  DOI: 10.1504/IJISE.2023.10059699
   
  
• Performance and Reliability Analysis of Pulping system in a Paper Plant  
  by Seema Sharma, Mamta . 
  Abstract: This paper presents the performance and reliability analysis of the pulping system in a repairable paper plant utilising the fuzzy y - method based on trapezoidal fuzzy numbers. The configuration of the pulping system has been modelled by the Petri net model. To deal with imprecision and vagueness in failure/repair data, trapezoidal fuzzy numbers are used to fuzzify the failure and repair data of each component of the pulping system. The fuzzy - method has been utilised to evaluate reliability factors of the pulping system including availability, reliability, failure rate, repair time, mean time between failures and expected number of failures at different spreads. The analysis is beneficial for plant managers to enhance the performance of the pulping system by developing and implementing appropriate maintenance strategies and policies.
  Keywords: repairable systems; fuzzy y λ-τ method; Petri net; trapezoidal fuzzy number; uncertain data.
  DOI: 10.1504/IJISE.2023.10059761
   
  
• Data-driven distributed control of input-coupled interconnected systems based on Nash optimality  
  by Dawei Zhang, Shouli Gao, Rui Xia, Dongya Zhao 
  Abstract: This paper introduces a data-driven distributed controller for interconnected systems with input coupling of unknown models. The estimation of input coupling terms does not depend on historical data. The complex interconnected systems with input couplings are decomposed into individual subsystems. The proposed strategy not only alleviates computational load, but also optimises the interaction between subsystems, effectively addressing the output oscillations of the system during abrupt reactions of input couplings. The convergence of the control algorithm and the stability of the closed-loop system response are examined, and the efficacy of the proposed control method is validated by comparative simulations.
  Keywords: input couplings; data-driven control; dynamic linearisation method; Nash optimality; distributed control.
  DOI: 10.1504/IJISE.2023.10059819
   
  
• Multi-period and multi-workday workforce scheduling for manufacturing workstations with multiple worker  
  by Tarit Rattanamanee, Suebsak Nanthavanij 
  Abstract: This paper discusses the complex workforce scheduling problem where a workday is divided into multiple periods and the planning horizon is extended to cover several workdays, or MPMW-WSP. Additionally, there can be multiple workers at individual manufacturing workstations. The MPMW-WSP focuses on the safe exposure of workers to a given ergonomic hazard that is dominantly present in the workplace. Dominant ergonomic hazard can be either a single-limit hazard or variable-limit hazard. A hybrid solution procedure is employed to solve the problem. It consists of a heuristic method to estimate an initial workforce size and an integer linear programming (ILP) model to determine a minimum number of workers to be rotated among different tasks so that their daily hazard exposures are within the permissible or recommended limit. Numerical examples and computation experiment are also presented.
  Keywords: workforce scheduling; job rotation; ergonomic hazard; hazard exposure; optimisation.
  DOI: 10.1504/IJISE.2023.10060406
   
  
• Impact of Interconnectivity and Information Sharing on Cyber-Physical System Implementation  
  by Mst. Nasima Bagum, Choudhury Abul Anam Rashed, Ratul Barman, Md. Ariful Islam, M.H. Kibria 
  Abstract: The study examines the correlation between implementing a cyber-physical system (CPS) and interconnectivity, information sharing and visibility (ISV). A conceptual model was developed based on an extensive literature review. The study was performed in a mixed mode based on the case study and survey. In the case study, ten public and private banks participated. The survey was conducted with responses from 54 banks using a semi-structured questionnaire. The conceptual model was validated, and the relationships within the model were tested using structural equation modelling (SEM). Additionally, the impact of CPS implementation on cost reduction, improved Performance, and enhanced resource utilisation was assessed. The data collected was analysed using SmartPLS 4. The findings indicated a positive influence of Interconnectivity and ISV on CPS implementation, leading to increased performance and resource utilisation. However, it is worth noting that the study did not find a positive effect of CPS implementation on overall cost.
  Keywords: interconnectivity; information sharing and visibility; ISV; cyber-physical system; CPS; conceptual model; structural equation modelling; SEM.
  DOI: 10.1504/IJISE.2023.10060663
   
  
• Improving satisfaction of waiting customers by personalized service  
  by Junxiang Li, Xiaran Gao, Chenglong Li, Xiaojia Ma 
  Abstract: Queuing problem is considerably important in a service field. The customers’ waiting satisfaction in the process of queuing has a large impact on the whole service. A queuing model providing personalised service is constructed to improve the satisfaction of waiting customers. The enterprise's extra service cost, waiting satisfaction and the customer's actual utility after service are analysed to increase the proportion of satisfied customers by using arena, a simulation software. By comparing with other queuing systems, the results show that the proportion of customers seeking personalised service, their willingness to get extra service and their queuing position of providing extra service have an important impact on the proportion of satisfied customers. The research can offer an important reference for contact centres and other service fields.
  Keywords: contact centre; personalised service; queuing theory; arena; waiting satisfaction.
  DOI: 10.1504/IJISE.2023.10060664
   
  
• Simulation Modelling and Comparison of different training algorithms for multistep prediction  
  by Ashwani Kharola 
  Abstract: This study investigates nonlinear autoregressive neural network (NARNET) and nonlinear autoregressive neural network with exogenous input (NARXNET)-based artificial neural network (ANN) models for multistep prediction of specific enthalpy of steam. Real-time experimental data on specific enthalpy of steam has been collected and used for training of proposed models. The machine learning models have been trained using different training algorithms namely Levenberg-Marquardt (LM), Bayesian-regularisation (BR), scaled-conjugate gradient (SCG), one step secant (OSS) and resilient back-propagation (RB). The prediction performance of these algorithms have been analysed in terms of root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bivariate correlation coefficient (COR) for a maximum step size of 30 multistep predictions. The results highlight superior performance of NARXNET model designed using BR-algorithm compared to prediction models designed using other training algorithms.
  Keywords: multistep prediction; NARNET; NARXNET; process modelling; simulation; training algorithms.
  DOI: 10.1504/IJISE.2023.10060838
   
  
• A bearing fault diagnosis and monitoring software system based on lightweight neural networks to resist coloured noise  
  by Wujiu Pan, Yinghao Sun, Shuming Cao, Kuishan Kong, Junyi Wang, Peng Nie 
  Abstract: In actual industrial sites, the application of bearings is becoming increasingly widespread. In order to better monitor the faults of bearings, this article combines the concept of deep learning and designs a bearing fault diagnosis and monitoring software system based on lightweight neural networks to resist coloured noise. This system is developed based on MATLAB App Designer. When testing the system, five different bearing datasets, namely MFPT, Paderborn, IMS, Ottawa, and CWRU, are applied. Considering that the data in actual scenarios contains complex noise, coloured noise signals are added. Compared to traditional fault diagnosis software that requires pre writing data into the program, this software can perform real-time processing on any single column vibration data file. By using lightweight neural network methods to preprocess the data collected by sensors, the SqueezeNet network has a faster speed to extract significant features of vibration. This software system can achieve time-frequency domain image output of signals, with multiple noise reduction methods. It can also calculate the frequency of faults based on bearing model data. Through envelope spectrum images, the location of faults can be monitored and email reminders can be sent to engineers.
  Keywords: lightweight neural networks; anti-coloured noise; software engineering; fault detect; system health management.
  DOI: 10.1504/IJISE.2023.10060844
   
  
• Reliability assessment of a NSP system under constant triangular fuzzy failure rates  
  by S. Malik, Suresh Chandra Malik, Naveen Nandal, A.D. Yadav 
  Abstract: Here, the reliability of a non-series-parallel system (NSP) has been examined considering fuzzy failure rates. There are seven non-identical components in the system, which are arranged into three structures. The two structures operate in parallel and each having three components connected in series; while the third structure has a single component connected with the extreme components of the parallel structures. The expression for reliability of the system is assessed using the path tracing method. The failure rate of the components is assumed as constant triangular fuzzy number and thus they follow the exponential distribution. The a-cut method is used to defuzzify these fuzzy numbers for determining reliability measures. The intervals for fuzzy reliability and MTSF of the system have been computed for both non-identical and identical components. An illustration of RLC system has been described to highlight the application part of the research work.
  Keywords: fuzzy reliability measures; NSP system; exponential failure laws; ?-cut approach; triangular membership function.
  DOI: 10.1504/IJISE.2023.10060854
   
  
• Unreliable Queue model with multi-Phases of services, Delay repair and Single vacation  
  by Binay Kumar 
  Abstract: In the present paper, we investigate a bulk queue model with unreliable server. The service is provided in multi phase; the first phase of service is essential for the entire arriving unit while remaining (l 1) services are optional and are provided as per demand of unit. The second phase of service is followed by first phase, third is followed by second and so on. The server may stops working during any phase of service due to random failure. The repair work starts immediately as soon as server fails, provided the repair facility is available, otherwise there may be delay in repair. The server takes single vacation as soon system becomes empty. After completion of vacation the server may turns on with probability p if there are N customers accumulated in the system, otherwise it may remain idle with probability (1 p). If there are more than N customers in the system then server immediately starts serving the waiting customer. The supplementary variable technique is applied to derive the servers state queue size distribution and queue size distribution at random epoch. The various performance measures of the system are obtained in explicit form. A numerical illustration is provided to verify the validity and sensitivity analysis of these performance measures.
  Keywords: : Optional Phase service; Supplementary variable; Unreliable server; Delay repair; policy.
  DOI: 10.1504/IJISE.2023.10061096
   
  
• Optimizing Multiple Sclerosis Detection: Harnessing Cutting-Edge MRI Image Analysis for Advanced Industrial Diagnosis  
  by Mohammed Obeidat, Hussam Alshraideh, Abedallah A.L. Kader, Rabah Al Abdi, Morad Etier, Nohammad Hamasha 
  Abstract: Human brain disorders are those abnormal changes that occur around or inside brain parts. These disorders include infections, tumours, trauma, degeneration, structural defects, stroke, and autoimmune disorders. The devastating consequences of brain disorders on the lives of humans could be reduced by early diagnosis. The diagnosis of brain disorders consumes higher time and effort by physicians compared to computerised diagnosis techniques. Several computerised diagnosis algorithms have been developed to improve and optimise the diagnostic capabilities of physicians. Magnetic resonance imaging (MRI) is an effective tool used for brain disorders diagnosis. MRI detection of multiple sclerosis (MS) is extremely complicated due to several reasons, including the anatomical variability between patients, lesion location, and the variability in lesion’s shape. This paper reviews several computerised algorithms used in diagnosing brain disorders, to present the most efficient techniques that reduce the physicians’ diagnosis time and effort of MRI images, hence, starting MS treatment at earlier stages.
  Keywords: magnetic resonance imaging; MRI; brain disorders; industrial engineering algorithms; decision; multiple sclerosis.
  DOI: 10.1504/IJISE.2023.10061152
   
  
• The impact of difficulty and expensive financing on energy industry conservation and emission reduction  
  by Zihan Xia 
  Abstract: This article separates the issues of financing difficulties and high financing costs, and studies the impact of financing difficulties and high financing costs on the energy-saving and emission reduction behaviour of enterprises. We find that when the problem of difficult financing for enterprises exists, the approved loan amount positively affects the level of energy conservation and emission reduction through production volume; The level of energy conservation and emission reduction is not related to the loan interest rate. The fixed cost investment in energy conservation and emission reduction is a major factor for enterprises to take energy conservation and emission reduction measures. Even with financing difficulties, because of the existence of carbon taxes and subsidies, companies tend to adopt energy-saving and emission reduction measures. The heterogeneity of enterprise scale only exists when financing difficulties exist. Once financing difficulties are resolved, there is no heterogeneity in the impact of enterprise scale on energy conservation and emission reduction levels. This means that the energy conservation and emission reduction levels of enterprises of different scales are ultimately the same.
  Keywords: difficulties in financing; high cost of financing; energy conservation and emission reduction; carbon tax; subsidy.
  DOI: 10.1504/IJISE.2023.10061208
   
  
• Optimizing Parcel Count in E-commerce Fulfillment with Mixed-Split Order Picking  
  by Wen Zhu, Jingran Zhang, Sanchoy Das 
  Abstract: E-commerce fulfilment warehouses (e-warehouses) store thousands of items and fulfil thousands of online customer orders every day. E-warehouses are operationally different from traditional warehouses. To accelerate fulfilment speed, an e-warehouse splits multi-line orders across multiple picklists. A key research question is how to manage the flow of picked items so that the number of shipped parcels is minimised. This research introduces the e-warehouse order consolidation (WOC) problem. Tote consolidation is a key link between order picking and parcel packing. We identify key modelling elements and formulate the associated constraints and objectives. The WOC mixed integer program is tested on a series of problems, and we illustrate the operational and business value of controlling the tote consolidation process. Order similarity between totes is used to develop two fast heuristics. Two controllable design parameters are investigated, the number of packing stations and the number of totes assigned simultaneously, on parcel packing efficiency.
  Keywords: fulfilment speed; shipping costs; parcel packing.
  DOI: 10.1504/IJISE.2023.10061212
   
  
• Jordan's Future Renewable Energy Stability and Break-even Analysis Under Various Catalysts Using System Dynamics  
  by Samer Abaddi 
  Abstract: The social acceptability of photovoltaic (PV) systems contributes not only to the amount of power generated but also to the CO2 emissions reduction in Jordan. The effect of three catalysts; subsidy proportion, Word of Mouth (WOM) and advertising effectiveness is addressed in this piece of work, in addition to a forecast of the power generated and the CO2 emissions reduction by 2080. System dynamics (SD) is the fundamental approach of this study. Qualitative interviews and energy reports assisted the data collection process and simulation was conducted between 2020 and 2080. Six scenarios are hypothesised to facilitate the comparison between the catalyst's effects with the help of break-even point analysis. Jordan is expected to generate 1.845 Terra Wh (TWh) and 995.9 TWh of energy by 2040 and 2080, respectively. The CO2 emissions reduction is expected to cross 630 million tons by 2080. Advertising effectiveness was found to be the top catalyst that stimulates the power generated in Jordan followed by WOM. The quantitative models foster the policy makers towards investing in social acceptability dimensions toward achieving earlier equivalency of demand and supply. This is the first study in Jordan that develops break-even calculations at various levels of catalysts using SD.
  Keywords: system dynamics; SD; power generated; word of mouth; WOM; subsidy proportion; advertising effectiveness; Jordan.
  DOI: 10.1504/IJISE.2023.10063431
   
  
• Resilience Optimization of Contact Centre under Emergencies  
  by Junxiang Li, Xiaran Gao, Xinping Shao 
  Abstract: Emergencies can easily block or paralyse the traditional contact centre system, and the routing strategy of the contact centre affects the ability of the system to deal with emergencies. In order to improve the handling capacity of the contact centre for emergencies and reduce economic losses, from the perspective of improving the resilience of the contact centre, a resilience index for quantitatively evaluating the resilience of the contact centre system during emergencies is proposed, and a new multi-channel contact centre model with distributed agents and artificial intelligence channels is established with the goal maximising the resilience index. The numerical simulation analysis and comparison of this model are carried out by ProModel, a simulation software package. The results show that the new model can reduce the number of customers who give up, improve the system resilience and cut the cost.
  Keywords: emergencies; contact centre; resilience; distributed agent; ProModel.
  DOI: 10.1504/IJISE.2023.10061214
   
  
• System Dynamics Costing Model for the Capital Cost Estimation of Electric Vehicle Batteries' Refurbishing Facility  
  by Ahmed Kalwar, Asif Wassan, Waleed Shaikh, Muhammad Ali Khan, Hussain Bux Marri 
  Abstract: Electric vehicles (EVs) are considered sustainable vehicles due to low carbon emissions. Lithium-ion batteries (LIBs) are expensive electrical vehicle batteries (EVBs) due to their expensive rare raw materials, i.e., lithium, nickel and cobalt. With increased production of EVs, authors warned of the expected huge quantity of dismantled EVBs shortly and so explored their reusability. An in-depth review is conducted, and system dynamics (SD) model was developed in Anylogic whereas origin was used for graphs. The capital costs dynamics of the refurbishing facility were evaluated and the model was validated and initialised. The analysis was conducted in three sales scenarios, i.e., 1) locally; 2) regionally; 3) nationally. This paper provides a framework for entrepreneurs. The results indicated scenario-2 as more suitable with a maximum return on investment (ROI) (80.26%) and minimum payback period (626 weeks). Therefore, it is concluded that it would be feasible for the refurbishing facility to operate regionally rather than locally/nationally.
  Keywords: electric vehicles; EVs; electric vehicle batteries; Lithium-ion batteries; LIBs; batteries; refurbishment; recycling; sustainability; carbon.
  DOI: 10.1504/IJISE.2023.10061280
   
  
• Development of Distributed LSTM Framework to Forecast Transportation Lead Time  
  by Utkarsh Mittal, Dilbagh Panchal 
  Abstract: This study aimed to develop an AI-based system to evaluate delivery complexities and reduce system vulnerabilities more accurately. The approach of the study is empirical where dataset from different systems is used to develop ML and DL models to forecast more accurately transportation time and improve profitability. Various models, e.g., linear regression, deep learning, and distributed long short-term memory (DLSTM) networks are used. It is found that the DLSTM regression model shows superior performance in forecasting the delivery times compared to the other models, achieving an accuracy of around 90%, as the model has the ability to handle complex and nonlinear relationships among variables. The findings underscore the potential of machine learning (ML) and deep learning (DL) in improving predictability and profitability aimed increasing digitalisation in global transportation.
  Keywords: machine learning; deep learning; delivery time forecasting; profitability optimisation; fuzzy C means clustering; supply chain risk management.
  DOI: 10.1504/IJISE.2023.10061303
   
  
• An Enhanced Fractional-order Fuzzy Controller Design for an Integrated Power System using a Counteractive Control Action  
  by Devbrat Gupta, Jitendra Kumar, Vishal Goyal 
  Abstract: This research article reports an efficient control of the Integrated Power System (IPS) using a fractional-order fuzzy proportional and derivative (FOFPD) controller combined with a fractional-order integral and derivative (FOID) controller in order to overcome the sudden variation in microgrid frequency problem. The novelty of the anticipated control strategy lies in the use of FOID control action, which generates the counteractive action to improve the control performance. The controller's gains are optimised by an optimisation algorithm called spider-monkey optimisation (SMO). The objective function is considered as the sum of the integral of the squared deviation of the microgrid frequency (ISFD). The proposed controller's response is then compared with the integer-order counterparts to investigate the effectiveness of the suggested controller. The detailed simulation results demonstrate the robust behaviour of the proposed control scheme and establish its superiority over other investigated control structures.
  Keywords: integrated power system; IPS; fractional-order; fuzzy PID controller; spider-monkey algorithm; micro-grid frequency.
  DOI: 10.1504/IJISE.2023.10061475
   
  
• PROMETHEE vs. OptQuest for simulation-based multi-objective optimisation approach in flexible manufacturing system  
  by Abdessalem Jerbi, Mohamed Ali ELLEUCH 
  Abstract: Flexible manufacturing system design is a complex problem because of its stochastic nature, especially when there are multiple optimisation objectives to consider. For this reason, various studies have relied on discrete event simulation tools to create and evaluate the flexible manufacturing system's performance using multi-objective optimisation methods. However, the literature lacks comparative studies of these different methods in the flexible manufacturing systems optimisation context. This paper aims to compare the two optimisation methods, PROMETHEE and OptQuest, based on multi-objective efficiency. PROMETHEE is based on ranking simulation results, while OptQuest is an iterative method using a meta-heuristic. This comparison showed that OptQuest is the best-performing method.
  Keywords: discrete event simulation; DES; multi-objective optimisation method; simulation-based; OptQuest; PROMETHEE; flexible manufacturing system; FMS.
  DOI: 10.1504/IJISE.2023.10061603
   
  
• Analyzing the Role of Multi-Agent Technology on High-Tech Manufacturing using AHP, DEMATEL, and TOPSIS  
  by Vikram Singh, Somesh Kumar Sharma 
  Abstract: High-tech product manufacturers operate in extremely sensitive environments and face challenges in meeting the quality standards of high-tech products. To address these challenges, this study aims analysing the impact of multi-agent technology (MAT) on the quality standards of high-tech manufacturing (HTM). The extensive literature was used to explore eight factors of HTM and forty-five variables of MAT. A hybrid multi-criteria decision-making technique was used to analyse the factors and variables. The HTM Process is a highly prioritised and impactful factor. Process monitoring, automatic customised test plans, adaptive agents, demand forecasting agents, and virtual manufacturing are the top five globally ranked variables. The findings of this article provide ranking order and determine the relationship between factors and variables for the integration of MAT in HTM. This bridging can assist designers in improving the design quality, manufacturers in increasing process quality standards of products, and market experts in selecting the potential market.
  Keywords: HTM; MAT; analytical hierarchy process; AHP; decision-making trail evaluation laboratory; DEMATEL; high-tech products; HTPs; technique for order preference by similarity to ideal solution; TOPSIS.
  DOI: 10.1504/IJISE.2023.10061604
   
  
• A Systematic Literature Network Analysis Approach to Assess the Topology of Modern-era Supply Chain Risk Management Research  
  by Leslie Dass, Sreerengan V.R. Nair, Georgy Kurien, Dr S. Kumar Chandar 
  Abstract: Over the past decade, there has been a significant increase in research on supply chain risk management (SCRM). This review uses a systematic literature network analysis to provide an overview of the SCRM research landscape, with emphasis on optimisation approaches, mathematical modelling tools, and the identification of seminal studies and relevant keywords used in SCRM research. However, there are few quantitative models that represent the relationship between supply chain surplus, sustainability, and resilience in SCRM literature. The study has limitations since it only sources from a single database, and more clarity is needed on the effectiveness of optimisation in SCRM, which can be further evaluated through case studies and empirical studies.
  Keywords: supply chain; risk management; optimisation; linear programming; resilience; sustainability; surplus; profitability.
  DOI: 10.1504/IJISE.2023.10061610
   
  
• Blockchain technology adoption in healthcare: a systematic review and conceptual framework  
  by Ashraf Abdou, Basma Ezzat, Sharif Mazen, Nagy Ramadan 
  Abstract: Recently, blockchain technology has attracted a lot of interest from different researchers and academics due to its unique properties like immutability, interoperability, and confidentiality. However, to date, their adoption in the healthcare sector is still very limited. Few studies applied a systematic literature review (SLR) for blockchain adoption in healthcare. In this research study, the first contribution is to identify the factors that influence the adoption of blockchain by applying the SLR approach, understand how these factors are interrelated, and discuss the main challenges of blockchain adoption. The findings demonstrated that, the unified theory of acceptance and use of technology (UTAUT), the technology acceptance model (TAM) and its extension were the most popular models used for blockchain adoption. Then, we identified the key research gaps and proposed a conceptual framework to address the identified gaps to be a reference and guide for organisations adopting blockchain in healthcare.
  Keywords: blockchain technology; healthcare; blockchain adoption; systematic literature review; SLR; UTAUT; technology acceptance model; TAM; TOE.
  DOI: 10.1504/IJISE.2023.10061699
   
  
• Portable Coconut Tree Climbing Device and its Analysis  
  by Ravi Kumar Mandava  
  Abstract: Coconut tree is one of the useful plant among all other plants. Due to the lack of coconut tree climbers worldwide, many coconut palm growers are not interested in cultivating coconut farming. Based on the above problem, numerous researchers have developed various climbing mechanisms. To overcome this problem a novel coconut tree climbing device (CTCD) was introduced which can climb the coconut tree up to the canopy. To check the deformation behaviour and generated stresses of various parts of the device in the present research work, the authors conducted dynamic analysis, such as modal, harmonic, and transient analysis in ANSYS 2021. Moreover, the dynamic properties of each component will also be tested under vibrational excitation. Therefore, one of the vibrational properties, that is, the natural frequency, is used to analyse the effect of transient loads and avoid the noise and vibration hazards in the components of the coconut tree climbing mechanism.
  Keywords: coconut tree climbing device; dynamic analysis; finite element method; ANSYS.
  DOI: 10.1504/IJISE.2023.10061804
   
  
• SDAPI: A Systematic Approach to Integrating Industry 4.0 and Lean Manufacturing for SME Improvement  
  by Hafsa El-Kaime, Saad Lissane Elha 
  Abstract: Many businesses, particularly small and medium-sized enterprises (SMEs), seek to improve productivity and reduce resource usage. Lean manufacturing (LM) is a popular method for optimising processes by eliminating non-value-added activities and improving efficiency and flexibility. However, in today's rapidly changing technological and market environment, companies must also adopt innovative production management approaches to stay competitive. The Fourth Industrial Revolution and related technologies offer the opportunity to take current manufacturing systems to the next level. While previous research has explored the concept of Lean 4.0, which combines Industry 4.0 and LM, there has been less focus on the relationship between methodological approaches and technological concepts. This research aims to fill this gap by presenting a methodological-technological framework for implementing Industry 4.0 technologies in SMEs in order to achieve the objectives of LM. The proposed methodology, called SDAPI, is developed through a literature reviews, it consists of five steps: specify, detect, analyse, propose, and implement.
  Keywords: framework; Industry 4.0; lean manufacturing; LM; Lean 4.0; small and medium-sized enterprises; SMEs.
  DOI: 10.1504/IJISE.2023.10061809
   
  
• Impact of Multi-Agent Technology on the Manufacturing Organizations: A Multi-Criteria Decision-Making Analysis  
  by Vikram Singh, Somesh Kumar Sharma, Prakhar Shukla 
  Abstract: Quality is a major concern for manufacturers and can affect the performance of manufacturing system components and product quality. This study aims to improve the quality of manufacturing processes from material acquisition to the end of production using multi-agent technology (MAT). The literature review identified five factors and their 31 governing variables, and their impact is analysed through AHP, DEMATEL, and TOPSIS. AHP was used to study and establish priority orders. DEMATEL was used to develop inter-relationship and TOPSIS to validate the global ranking evolved through AHP. Manufacturing Process along with Quality Aspects are evolved most significant factors for controlling quality. Their significance is increased since they were discovered to be the most influential in affecting other factors. The detailed research and discussions in this article may allow industrial organisations to raise quality standards, hence increasing customer support, lowering costs, and improving efficiency.
  Keywords: analytic hierarchy process; AHP; DEMATEL; manufacturing organisational; multi-agent technology; MAT; TOPSIS.
  DOI: 10.1504/IJISE.2023.10062063
   
  
• Customer Behavior Analytics in A Supermarket in Taiwan Based on RFM Model  
  by Mei-Wei Huang, Hao-Wei Yang, Ming-Min Lo, Yung-Tai Tang, Hsin-Hung Wu 
  Abstract: Supermarkets need to use a data-driven approach to segment customers based on their purchase transactions to meet different customer needs in this highly competitive retail industry in Taiwan. This empirical study combines clustering techniques and RFM model to analyse member customers' transaction data from a database of a supermarket in Taiwan within a six-week period. The results showed that 5,410 member customers are grouped into loyal, new, and vulnerable customers. A one-way analysis of variance is performed to show these three groups of customers are statistically different. This research further explores the top 10 best-selling merchandise items in both purchase quantity and total money spent. Loyal customers need to focus on five merchandise items. New customers have eight out of ten best-selling merchandise items appeared in both purchase quantity and total money spent. Supermarket management need to pay more attention to these eight items for new customers in this supermarket.
  Keywords: customer behaviour; supermarket; RFM model; data-driven approach; loyal customer; new customer; vulnerable customer; best-selling merchandise items; Taiwan.
  DOI: 10.1504/IJISE.2023.10062080
   
  
• Ranking of factors affecting performance of manufacturing industry using Fuzzy MAUT technique  
  by Rajdeep Singh, Chandan Deep Singh 
  Abstract: With the rise of creative engineering, India's manufacturing industry is expanding quickly. Because of this, the market is more cutthroat for businesses, especially those that are indigenous. Core functional competences are essential for survival in the age of globalisation since they can positively or negatively impact a variety of organisational performance factors. This paper deals with the prioritisation or ranking of the factors which affect core functional competencies and further affect the performance of Indian manufacturing industry. For the ranking of the attributes fuzzy MAUT method has been used in the study.
  Keywords: fuzzy MAUT; core functional competencies; competitiveness; globalisation.
  DOI: 10.1504/IJISE.2023.10062495
   
  
• Particle Swarm of Optimisation Strategy for Design Optimisation of a Series-Parallel System Incorporating Failure Dependencies and Multiple Repair Teams  
  by Himani Pant, S.B. Singh 
  Abstract: A series-parallel system with multiple repair teams and failure dependence is investigated in this article. An optimal design problem is being scrutinised and worked upon in the current paper. This work is conducted in reference to prior study conducted by Hu et al. (2012). They used genetic algorithm (GA) to find the optimal design of the seriesparallel configuration consequently minimising its cost. The particle swarm optimisation (PSO) technique is being proposed in this article to further refine their results. The solution entails identifying the vector comprising of system components and repair teams, (n1, n2, , nN, r1, r2, , rN). These computations were carried out using the computer software Python. As a consequence, extremely intriguing results were achieved.
  Keywords: particle swarm optimisation; PSO; design optimisation; series-parallel configuration; failure dependencies.
  DOI: 10.1504/IJISE.2023.10062574
   
  
• Sustainable Spare Parts Inventory Stock Control Management at Macro Level, using Linear Programming: Perspective to Petroleum & Fertiliser Industries  
  by Sandeep Sharda, Sanjeev Mishra, Dheeraj Nimawat 
  Abstract: The goal of the study is to manage the problem in the petroleum and fertiliser sectors by optimising the overall spare parts inventory. To solve the issue, the proposed framework employs the linear programming model (LPM) and TORA software to optimise the entire spare parts inventory. This research offers petroleum and fertiliser industries a clear and straightforward way for the spare parts management. Results show improved cost and stock management that promotes sustainability with optimised data set of total spare parts inventory as 40,000 numbers and US$65.5 million. Additionally, it eliminates the excessive stock due to exaggerated risk with traditional practices and reduces deterioration by lowering long-stay of items in the warehouse. Validation of model is done using classified data sets (as HML and FSN) that are based on previous factual six years' cumulative consumption and acquired from an Indian fertiliser industry.
  Keywords: high; medium and low; HML; sustainability; spare parts macro inventory; linear programming; LP; TORA; fast; slow and non-moving; FSN.
  DOI: 10.1504/IJISE.2023.10062575
   
  
• Exploring Evolution, Development, and Contribution of International Journal of Industrial and Systems Engineering (2005-2022): A Bibliometric Study  
  by Santosh Baheti 
  Abstract: International Journal of Industrial and Systems Engineering (IJISE) reached its 18th year of publishing in 2023. A comprehensive assessment of 1,096 publications using the bibliometric data analysis technique is performed to understand growth of the journal for the past 18 years. Different indicators like co-occurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS Viewer software. The findings of the study emphasise contribution of IJISE to knowledge domain.
  Keywords: bibliometrics; Scopus; industrial management; system engineering; VOS viewer.
  DOI: 10.1504/IJISE.2023.10062586
   
  
• A comprehensive approach to UA Facility Layout Design Using Genetic Algorithm  
  by Kamal Deep 
  Abstract: Facility layout panning is a quantum leap for the production industry to realise the low entropy, widely applied to the unequal area facility layout problems (UA-FLPs). This paper aims at the optimisation of UA-facility layout in the flexible bays structure (FBS) to maximise the adjacency requirements of facility types for the production layout. The FBS is a most commonly used structure flexible to allocate the facilities in the bays of unequal areas permitting empty space in the total area of the layout. The proposed mixed integer programming model has been formulated to ensure; minimum side length, confined aspect ratio of facility types, and optimal space utilisation in the total area of facility layout. The genetic algorithm based heuristic has been used to search the discrete solution space in a feasible time span. The optimal results obtained are mapped with the best known numerical instances reported in the literature to approve the efficacy of proposed solution approach.
  Keywords: unequal area facility layout; flexible-shape facilities; genetic algorithm-based optimisation algorithm; flexible bays structure; FBS.
  DOI: 10.1504/IJISE.2024.10062606
   
  
• Trajectory prediction using inference model  
  by Yun-xiang HAN 
  Abstract: With the rapid increase in air traffic, more accurate aircraft trajectory prediction is the focus of integrated airspace operations for both manned and unmanned civil aviation. The development of machine learning technology is expected to bring new solutions to this problem. This paper processes and analyses aircraft trajectory data, and models aircraft trajectory prediction based on hidden Markov models, providing an efficient and accurate solution for aircraft trajectory prediction. Firstly, the trajectory data was pre-processed to provide effective support for the subsequent model formulation. Secondly, a trajectory prediction model was designed using the trajectory data and hidden Markov model. Finally, the performance of different models was compared and analysed through experiments.
  Keywords: trajectory prediction; air traffic management; system modelling; simulation.
  DOI: 10.1504/IJISE.2023.10062927
   
  
• Multi-Objective Optimization in Turning AISI 304 Stainless Steel: An Integration of The Taguchi Method, Response Surface Methodology, and NSGA-II  
  by Cong Chi Tran, Thi Tham Nguyen, Van Tuu Nguyen 
  Abstract: This study examined the impact of machining parameters [depth of cut (d), feed rate (f), and spindle speed (s)] on surface roughness and material removal rate in the turning process of AISI 304 stainless steel. Three optimisation methods were used: the Taguchi method, the response surface methodology (RSM), and the non-dominated sorting genetic algorithm II (NSGA-II). The Taguchi method identified the most influential parameter for surface roughness (f > d > s) and for material removal rate (d > f > s). RSM regression models achieved high R2 values of 0.9896 for roughness and 0.9997 for material removal rate. NSGA-II multi-objective optimisation produced 35 Pareto solutions within ranges of cutting parameters, resulting in surface roughness values from 0.239 to 3.301 ?m and material removal rates from 151.53 to 594.99 mm3/s. Confirmation experiments validated the optimal values, with deviations within 10%, confirming the accuracy of the research method for solving the optimisation problem.
  Keywords: multi-objective optimisation; 304 stainless steel; Taguchi method; response surface methodology; RSM; NSGA-II.
  DOI: 10.1504/IJISE.2024.10062971
   
  
• Reliability Analysis of Bleaching System in a Paper Industry  
  by Seema Sharma, Mamta . 
  Abstract: This paper presents a fuzzy technique to examine the reliability of bleaching system in a paper industry using uncertain data. The uncertainties in failure/repair data of every subsystem/component of the bleaching system are quantified using two types of fuzzy numbers, trapezoidal and triangular fuzzy numbers. The basic arrangement of components/subsystems of bleaching system is represented using Petri net model. The fuzzy values of various reliability metrics of bleaching system for different uncertainty levels have been evaluated employing fuzzy - technique. Subsequently, to analyse the failure behaviour of bleaching system and to plan for suitable maintenance policies, these fuzzy values have been defuzzified using centre of area method. The analysis is useful for plant managers to improve the performance of bleaching system by establishing and implementing appropriate maintenance strategies and policies.
  Keywords: reliability analysis; uncertain data; Petri net; fuzzy methodology; trapezoidal fuzzy number.
  DOI: 10.1504/IJISE.2024.10063077
   
  
• Integration of Kansei Engineering and Artificial Neural Network Towards the Implementation of Intelligent Food Packaging Design Based on Consumer Preferences  
  by Sakir Sakir, Bambang Dwi Argo, Yusuf Hendrawan, Sugiono Sugiono 
  Abstract: Packaging design innovation is one of the crucial strategies for consumer-oriented product development. Therefore, this research aimed to design intelligent food packaging (IFP) for beef products using an integrated approach of Kansei engineering (KE) and artificial neural network (ANN) based on consumer preferences. The results showed 37 valid and reliable Kansei words based on Kaiser-Meyer-Olkin measure (KMO), Bartlett’s test of sphericity, and measure of sampling adequacy (MSA) using SPSS 26 software. Based on the results, the best ANN structure was achieved with the Traingd learning algorithm which had 418 inputs, 20 nodes in the hidden layer, and eight outputs with a training mean square error (MSE) of 0.0099991, a validation MSE of 0.0321, a training regression (R) of 0.99287, and a validation R of 0.98928. Therefore, the best IFP design for beef products based on consumer preferences could be achieved by integrating KE and ANN methods.
  Keywords: Kansei engineering; artificial neural network; intelligent food packaging design; consumer preferences.
  DOI: 10.1504/IJISE.2023.10063165
   
  
• A Hybrid Optimisation Strategy for Large-Scale Vehicle Routing Problems with Time Windows using Solution Initialisation  
  by Yongzhong Wu, Minqi Xu, Mianmian Huang 
  Abstract: This paper investigates a novel hybrid optimisation strategy that integrates a machine learning algorithm with a meta-heuristics to tackle large-scale vehicle routing problems with time windows (VRPTW). Specifically, the K-means clustering algorithm is employed to generate initial routing solutions, subsequently optimised by an artificial bee colony (ABC) algorithm. The new approach is tested on large-scale real-life cases. The computational results show that the new algorithm outperforms a well-established ABC algorithm in terms of both objective value and computation time. In addition, the experiments highlight the importance of considering both the distance between customers and customer time windows in the clustering process to ensure good computational results.
  Keywords: vehicle routing problem with time windows; clustering; artificial bee colony algorithm.
  DOI: 10.1504/IJISE.2024.10063184
   
  
• Designing and Assessing Cognitive Training Application for Seniors with MCI: Comprehensive Evaluation Methodology  
  by Dong Zhang, Yazhen Lan, Shan Hu 
  Abstract: This study addresses the absence of design standards for cognitive training apps catering to seniors with mild cognitive impairment (MCI). Integrating qualitative and quantitative methods, it employs grounded theory (GT) for synthesising user interview data and iteratively refines design criteria through theoretical coding. The fuzzy analytic hierarchy process (FAHP) and criteria importance through intercriteria correlation (CRITIC) objectively establish weights for design evaluation criteria and finalise the weighting values using the combined ideal point assignment method. The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is used to evaluate and select design solutions. This comprehensive approach minimises subjectivity and bias in criteria determination and weighting, enhancing the Objectivity and accuracy of cognitive training application evaluations. Usability questionnaires and user testing validate that the integrated approach improves design decisions' objectivity and scientificity, making the application more responsive to user needs.
  Keywords: healthy ageing; cognitive training; mild cognitive impairment; MCI; grounded theory; evaluation methodology.
  DOI: 10.1504/IJISE.2024.10063243
   
  
• Variant-Rich New Energy Vehicle Powertrain Functional Safety Engineering  
  by Roland Mader 
  Abstract: New energy vehicles (NEVs) are a success story that has led to the continuous introduction of manifold vehicle models and variants. Due to the fact that NEV powertrains are controlled by E/E (electrical and/or electronic) systems, faults and failures of these systems can lead to hazards. In order to prevent such hazards, functional safety engineering aims at avoiding or mitigating safety-critical E/E system faults and failures on the system, hardware and software level. Accordingly, numerous functional safety activities need to be executed and many workproducts are required. Variability of NEVs, high requirements as to achieve functional safety, short development cycles and resource constraints impose challenges for automotive companies. Motivated by an industrial case study we identify variation points of NEV powertrains and analyse their dependencies on the functional safety lifecycle. Based on that, we identify organisational and technical measures which support variant-rich new energy vehicle powertrain functional safety engineering.
  Keywords: Functional Safety; New Energy Vehicle; Battery Electric Vehicle; Hybrid Electric Vehicle; Powertrain; E/E System; Product Line; Variability.
  DOI: 10.1504/IJISE.2023.10063252
   
  
• Optimal operation of microgrid systems considering user energy storage behavior  
  by Junxiang Li, Chenmin Gong, Deqiang Qu, Xi Wang 
  Abstract: This paper establishes a microgrid system optimisation model based on carbon capture and shared energy storage to promote new energy consumption and better reduce carbon emissions. Considering the user's psychology and demand response, the energy storage behaviour of users is analysed to maximise the benefit of energy storage and achieve a win-win situation for both load aggregators and shared energy storage providers. The pricing and energy supply strategies of microgrid operators are optimised based on carbon capture technology. A case study is conducted on a microgrid system located in a business park in southern China. Through numerical simulation and comparative analysis of multiple scenes, it is verified that carbon capture devices and shared energy storage can significantly reduce the microgrid's carbon emissions and the uncertainty of the system operation and improve users'; demand response capability, which is beneficial to the long-term development of the microgrid system.
  Keywords: carbon capture; shared energy storage; demand response; user psychology; energy storage behaviour.
  DOI: 10.1504/IJISE.2024.10063438
   
  
• Effects of building parameters on mechanical and surface properties of 3D printed bioplastic (PLA) using TOPSIS: An experimental study  
  by Senthil S. M, Bhuvanesh Kumar M, Rajeshkumar L, Sampada Viraj Dravid 
  Abstract: Additive manufacturing is becoming an emerging technology in manufacturing three dimensional (3D) components in a layer-by-layer printing fashion. The technology enables wide variety of materials to be printed for different applications starting from automotive, aerospace, marine and to the biomedical fields. 3D printing processes are majorly used to print polymeric materials compared to metallic materials. Polylactic acid (PLA) is the most commonly used material by the fused deposition modelling technique, which accounts for multiple applications. The present study investigates the effect of printing parameters such as infill density, wall thickness, printing speed and ironing to identify optimum process parameter combination for better mechanical performance. Based on the design of experiments, 40 samples were printed and measured for mechanical characteristics. Upon the analysis using TOPSIS, at the parameter combination of infill density (99%), wall thickness (3 mm), and printing speed (150 mm/hr), the printed specimens showed higher tensile strength of 10.20 MPa and comparatively good surface finish. Hence the parameter optimisation showed a positive influence on enhancing the mechanical properties of printed components.
  Keywords: 3D printing; additive manufacturing; polylactic acid; PLA; parameter optimisation; TOPSIS.
  DOI: 10.1504/IJISE.2024.10063451
   
  
• A Study on the Application of Emotional Factors in Medical Products for Paediatric Asthma  
  by Jun Wang, Yazhen Lan, Dong Zhang, Mengqing Liu 
  Abstract: Emotional factors play a pivotal role in enhancing the user experience of medical products for paediatric asthma, mitigating children's negative emotions, and improving treatment adherence. However, a comprehensive framework and assessment criteria for integrating emotional factors into the design of such medical products are lacking. To standardise these criteria, this study integrates emotional design theory, grounded theory, and the fuzzy analytic hierarchy process (FAHP). Firstly, based on the three-level theory of emotional design, an interview outline was constructed to conduct semi-structured interviews with the target users, and the interview content was coded and analysed using the grounded theory to refine the emotional factor design indicators. Subsequently, FAHP assigned weights to these indicators, constructing a comprehensive emotional factor application model. PSSUQ validated product usability, revealing that the proposed model effectively meets users’ emotional needs, thereby standardising emotional factors application criteria and offering theoretical references for designing medical products for paediatric asthma.
  Keywords: emotional factors; emotional design theory; grounded theory; fuzzy analytic hierarchy process; FAHP; paediatric asthma medical products.
  DOI: 10.1504/IJISE.2024.10063622
   
  
• Lean Manufacturing applied in developing countries: a case study in metal industry  
  by Abror Hoshimov, Anna C. Cagliano, Jamshid Inoyatkhodjaev, Antonio Carlin 
  Abstract: This paper proposes a structured approach integrating the main Lean Manufacturing tools to improve the operational performances of companies in developing countries, particularly in Central Asia. A case study approach is applied to a manufacturing company in Uzbekistan. Four steps are performed: selecting a case company; creating a working team and defining the current process mapping; selecting the relevant key performance indicators and Lean tools; implementing Lean tools and assessing improvements. The overall daily production rate of the case company increased by about 28% after Lean application. Developing countries need specific efforts to overcome the barriers related to the cultural background of companies and mentality of their employees, in order to support Lean Manufacturing diffusion. This case study can stimulate academicians focusing on further research about the application of Lean tools in developing countries and the key contextual drivers of its successful implementation.
  Keywords: Lean Manufacturing; Value Stream Mapping; 5S; Developing Countries; Case study; Uzbekistan.
  DOI: 10.1504/IJISE.2024.10063624
   
  
• A revenue-based decision-making approach for evaluating modular product release plans under resource constraints  
  by Adewole Adegbola, Venkat Allada 
  Abstract: This study introduces the module substitution concept to develop an approach for assessing different strategies for modular product release in a technology-receptive market. We consider a situation where product variants emerge from modules which have varying modular relationships, and each module is defined by specific attributes. The statistical program evaluation and review technique (statistical PERT) was then adopted to address the uncertainties associated with module attributes. A practical example involving the development of modules, product families and their product variants is used to demonstrate the applicability of the approach in which feasible strategies that satisfy the development resource constraint were identified. We then introduced a substitute module to yield a product variant and re-evaluated the strategies. The results obtained shows that the approach is instrumental in assessing various alternatives based on launch timings and revenue generation and can be adopted by managers in deciding on the appropriate product release plan.
  Keywords: product release; product variants; resource constraint; module substitution; statistical PERT.
  DOI: 10.1504/IJISE.2022.10050936
   
  
• A multi-objective optimisation for green supply chain network design problem considering economic and environmental sustainability  
  by Sreyneath Chhun, Saowanit Lekhavat, Mohammad Alghababsheh 
  Abstract: The aim of this study is to develop a multi-objective optimisation for the green supply chain network design (GSCND) problem considering economic and environmental sustainability. The economic and environmental sustainability of different facilities (i.e., suppliers, plants and distribution centres) and allocation routes under five different scenarios of demand, capacity, distance, and area were evaluated. The economic sustainability was assessed in terms of four supply chain costs (i.e., establishment, transportation, production and holding costs). Environmental sustainability was measured using the ReCipe method - a method of life cycle assessment (LCA). The result revealed an interesting practical solution to the scenarios considered.
  Keywords: environmental sustainability; green supply chain; multi-commodity; multi-objective optimisation; particle swarm optimisation; supply chain network design problem.
  DOI: 10.1504/IJISE.2022.10050355
   
  
• Development of a face shield concept to protect against COVID-19 infection using integrated CAD and CAE tools and sustainable design techniques: deployment of international standards  
  by Nasser Ramsawak, Boppana V. Chowdary 
  Abstract: To this day, the COVID-19 pandemic has infected hundreds of millions of persons globally. Counter measures to combat this virus have been orchestrated by major health enterprises that have approved solutions including vaccines, social distancing and facial protection. As such, this paper focuses on the development of a COVID-19 preventative face shield concept using integrated computer-aided design and engineering (CAD and CAE or CAD/E) tools alongside sustainable design techniques to generate a virtual model in compliance with the safety standards as recommended by the major international health organisations. The study will employ an extensive review of literature, standard product development practices, CAD drawings, and CAE simulations and analysis to facilitate the concept's evolution. This proposal can prove highly valuable to sanitation companies owing to the recently exorbitant market demands for face shields because of the pandemic, which can in turn provide substantial profit to both a business and daily consumer.
  Keywords: COVID-19; face shield concept; computer aided design; CAD; computer aided engineering; CAE; sustainable design techniques; safety standards; product development practices; health organisations; virtual model; sanitation companies.
  DOI: 10.1504/IJISE.2022.10050343
   
  
• Lean manufacturing implementation in the food industry in Jordan  
  by Lubna A. Baqleh, Hala AlSliti, Mohammed Said Obeidat, Samir Khrais 
  Abstract: Lean manufacturing philosophy aims to enhance operation efficiency by eliminating wastes, which are considered non-value added activities that increase costs and reduce profits in the competitive marketplace. In this study, the lean manufacturing concepts were used using the value stream mapping, to highlight areas of improvement and eliminate wastes in a thyme manufacturing line in a food factory in Jordan. The data were collected using motion and time study concepts from the factory, and both the current and future state value stream maps were constructed. The results showed that when joining packing and labelling operations in the thyme manufacturing line, the lead time was successfully reduced by 13.57%.
  Keywords: lean manufacturing; value stream mapping; VSM; thyme; food industry; Jordan.
  DOI: 10.1504/IJISE.2022.10050436
   
  
• Development of a prescription framework for supply chain risk management: cases of Asian MNCs  
  by Jae-Yong Yang, Geun-Wan Park, Kwangtae Park, Rajesh Piplani 
  Abstract: We use the level of impact and duration of risk to classify types of supply chain risks and their effective prescriptions using case studies of multi-national companies. The classification of supply chain risks and countermeasures for each risk type are presented as a risk diagnosis and prescription matrix. The companies adopt a risk acceptance strategy when the impact is low and the duration short. When impact is high and the duration short, substitute raw materials (or production sites) are considered under risk avoidance strategy. New suppliers and technologies are developed for complete replacement for risk mitigation when the duration of risk is long but the impact low. For risk-sharing, new demand sources are developed, and diversification of suppliers and production sites pursued when the risk duration is long and the impact high. Novelty of our study is in considering risk duration as an additional variable in risk management strategy.
  Keywords: supply chain risk; prescription matrix; Asian MNC.
  DOI: 10.1504/IJISE.2022.10051409
   
  
• Ergonomics intervention with DMAIC methodology application - a case study in the food manufacturing industry  
  by Nur Nadia Nadirah Yusuf, Shaliza Azreen Mustafa, Rosmaini Ahmad 
  Abstract: This study aims to assess the level of ergonomics risk factors (ERFs) in production workstations using ergonomics assessment tools and provide an appropriate solution to improve the safety and health of the workers. A systematic approach using define-measure-analyse-improve-control (DMAIC) methodology was applied. Initial assessment found that awkward posture was the main ERF emerging in the company. Under the Measure and Analyse phases, the rapid upper limb assessment (RULA) and rapid entire body assessment (REBA) tools were applied to further assess of the identified ERFs. Results found that the filling task is the highest risk condition. Improve phase involved improvements action based on simple invention using a wooden step stool to provide a neutral working posture and the REBA has showed the signs of low risk comparatively. Related recommendations based on hazard identification, risk assessment and risk control (HIRARC) were then given in the control phase for future work planning.
  Keywords: ergonomics assessment; musculoskeletal disorders; MSD; DMAIC; RULA; REBA; food industry.
  DOI: 10.1504/IJISE.2022.10050938
   
  
• Construction of Prediction Model for Individual Investors’ Psychology and Behavior Based on Cognitive Neuroscience  
  by Guangdong Liu, Sang Fu, Shiyong Liu 
  Abstract: Traditional forecasting models cannot extract the trend information of retail investors' multi-scale psychological and behavioural data, and the predictions are not accurate. To solve this problem, a Markov-based individual investor psychology and behaviour prediction model is proposed. Using the wavelet multi-scale analysis method , the multi-scale data of individual investor's psychology and behaviour are extracted. A long-term-memory analysis is performed on multi-scale data of individual investors’ psychology and behaviour using the correlation analysis method, and the trend information is extracted. On this basis, a Markov prediction model is established, and a modified investment preference model is introduced to improve the accuracy of the prediction. Using the individual similarity degree, the nearest neighbour set of the target individual is established, and a multi-order predictive Markov fusion model for multiple individuals is formed to achieve accurate prediction. The experimental results show that the proposed model achieves better nonlinear fitting and higher prediction accuracy.
  Keywords: individual investors; psychology and behaviour; prediction model; Markov.
  DOI: 10.1504/IJISE.2022.10046762