International Journal of Industrial and Systems Engineering (80 papers in press)
Benchmarking Model to Analyse ISCM Performance of Selected Indian Manufacturing Industries using Fuzzy AHP Technique
by Kailash, Rajeev Kumar Saha, Sanjeev Goyal
Abstract: Competing globally with world class industries, Indian manufacturing industries need to brace itself with benchmarking models and continuous self-improvement. Internal supply chain management (ISCM) performance may be focussed in particular to create a niche over others. Proper understanding of key performance indicators of ISCM is necessary to analyse the gaps. A suitable methodology is also required to interpret the loopholes in order to remove them. A combined approach of fuzzy logic and analytic hierarchy process (AHP) technique is used for better result of theoretical benchmarking model. Comparison control bar charts are also used to view the performance gap between internal supply chains of selected manufacturing competitors. The primary purpose of this paper is to identify worst performance measures by implementation of benchmarking model, fuzzy logic and AHP methodology.
Keywords: ISCM; KPI’s; benchmarking model; Fuzzy logic; MCDM; AHP technique.
Comparative Analysis of Different Vedic Algorithms for 8
by Rana Majumdar
Abstract: Multipliers are the basic building blocks of various processors; arithmetic and logical unit and they are widely used in digital signal processing and image processing applications such as convolution, DWT, DCT. In this paper, four separate algorithms for designing binary multipliers are adopted from the ancient Indian Book of Wisdom Sthapatya-veda (an Upa-veda of Atharvaveda). The current work mainly focuses on comparing the power, delay, LUTs (look up table), noise margin of different multiplier algorithms using various sutras of Vedic mathematics which has been implemented on Virtex 7 Board 1.1, using Xilinx Vivado version 14.2
Keywords: Delay; LUT; Power; Vedic Multiplier.
Identification of key lean practices within Indian automotive SMEs environment
by Rupesh Tiwari, Jeetendra Tiwari
Abstract: Purpose: SMEs are backbone of Indian economy, contributing more than 20 percent to GDP and providing employment to nearly 50 million people. With the increasing globalization, Indian SMEs (Small & medium-sized enterprises) are facing stiff competition both in and out of the county by the big players in particular. Indian SMEs are suffering from scarcity of vital resources and latest technical knowhow. Its imperative for them to use resources judiciously by implementing lean manufacturing. Its not feasible for SMEs to implement all the lean practices like big players. The objective of current study is to identify key lean practices for the Indian automotive SMEs to reap the maximum benefits out of it. Factor analysis was applied to identify independent lean practices because the various lean practices suggested by the different researchers are found overlapping and confusing in nature. Multiple regression analysis is used to identify the key lean practices which Indian SMEs can afford and must implement. Customer involvement is the most important practice followed by problem identification & prevention, total productive maintenance, and others. The novelty of this study emerges from identification of key lean practices within automotive Indian SMEs environment using statistical analysis. The finding of this study will serve as vital input for lean functional deployment.
Keywords: Lean manufacturing; Key lean practices; Factor analysis; Multiple regression; Sustainable strategic advantages; Small & Medium sized enterprises.
AN ALGEBRA APPROACH FOR NONLINEAR MULTIVARIABLE FED-BATCH BIOPROCESS CONTROL
by María Cecilia Fernández, Maria Nadia Pantano, Santiago Rómoli, Daniel Patino, Oscar Alberto Ortiz, Gustavo Scaglia
Abstract: In this paper, a linear algebra based controller design is proposed. This technique allows tracking, with minimum error, predefined optimal profiles in nonlinear and multivariable systems. To achieve this, control actions are obtained solving a linear equation system. The controller parameters are selected with a Monte Carlo algorithm. The methodology is applied in a fed-batch penicillin production process, where the control action is the feed flow rate and the tracked profiles are the concentration of biomass, product and subtract inside the reactor. Different tests are shown to prove the good performance of the controller adding: parametric uncertainty and perturbations in the control action and in the initial conditions.
Keywords: Nonlinear dynamics control; fed-batch fermentation; penicillin production; profiles tracking control.
Simulation-based Optimization Model for Paired-cells Overlapping Loops of Cards with Authorization (POLCA) system
by Saeed Abdolmaleki, Masoud Kasaee, Sajjad Shokouhyar
Abstract: Companies with high variety of high-mix products are interested in having smoother production flow to cope with tardiness, to this end, they have been looking for an effective Production and Material Flow Control (PMFC) system to gain competitive advantages. In practice, Paired-cells Overlapping Loops of Cards with Authorization (POLCA) system has had a great remarkable success. This paper deals with a simulation-optimization approach to evaluate POLCA control system in workshops before implementing it.
Keywords: Discrete Event Simulation; Optimization; POLCA.
Using simulation to reshape the maintenance systems of caster segments
by Rossella Pozzi, Margherita Pero, Roberto Cigolini, Francesco Zaglio, Tommaso Rossi
Abstract: The maintenance of steel mills has a relevant impact on costs and productivity of steel industry. Caster segments are the key components of the slab caster and they have to be maintained on a regular basis to ensure a high steel quality. According to the traditional approach, one crew per shift takes care of the maintenance of each segment. This way of doing requires the operators to be skilled in all the phases needed to repair a segment, while process control is very limited and performance indexes (productivity, lead-time, etc.) hit very low levels. This paper introduces a new approach to repair caster segments that makes each segment move along a disassembly and then assembly line where specific attention has to be paid to shared resources. The methodological approach is based on simulation, which has been applied to a real-life case study, represented by a leading Indian steel mill. Simulation is exploited, first, to point out the effect of the concurrent requirement of resources, demonstrating that a static sizing can lead to wrong designs, then, to properly consider the variance of execution times. Results show that caster maintenance arranged in a line designed according to the proposed methodology remarkably contributes to speed up the maintenance process and that the number of segments needed to run the line is reduced, leading to a corresponding reduction of operative working capital by about 16 million $.
Keywords: Simulation; maintenance; steel mills; flow line.
Scheduling an Assembly Job Shop Production System with Multiple Objectives: A Simulation Study
by Midhun Paul, R. Sridharan, Radha Ramanan T
Abstract: This paper presents the salient aspects of the performance analysis of two mechanisms for shop floor control namely; Order Review/ Release (ORR) and dispatching rules in an assembly job shop system in a multi-objective environment. A simulation model of an assembly job shop is developed for experimentation with eight dispatching rules and four ORR mechanisms from the literature. An ORR policy based on the concept of backward scheduling and interval release is developed and incorporated in the simulation model. Grey relational analysis is used for ranking the ORR policy-dispatching rule combinations. Multivariate and univariate hypotheses are developed. The results are analyzed using ANOVA and MANOVA. Grey relational analysis used for ranking the ORR policies-dispatching rule combinations. The results are subjected to univariate and multivariate hypotheses. The analysis of results reveals integrating dispatching rules with ORR policies provides better system performance than using dispatching rules alone. The proposed ORR policy namely, backward scheduling with interval release policy provides better results than other ORR polices.
Keywords: Assembly Job Shop; Simulation; Scheduling; Multi-Objective; GRA.
Analytical Approximations to Predict Order Picking Times at a Warehouse
by Maria Hulett, Purushothaman Damodaran
Abstract: The primary objective of this research was to develop analytical approximations to predict the time taken to complete a customer order in a warehouse. The problem under study was modeled as a network of queues and the parametric decomposition approach was adopted to develop the approximations. Under this method, the queuing network is decomposed into individual queues allowing to analyze single (i.e. customer order processing, pallet building, and re-pick process) and fork-join stations (i.e. order picking with synchronization constraints) within the same framework. Analytical formulations to estimate order picking times were developed and compared with equivalent simulation models to estimate the accuracy of the formulations. Appropriate correction terms were also developed to bridge the gap between the analytical approximations and the simulation models. The experimental study conducted indicates that the analytical approximations along with the correction terms can serve as a good estimate for the order picking times in a warehouse.
Keywords: Queuing networks; Parametric decomposition approach; Fork and join queues; Warehouse order picking;Analytical formulations; Markovian Systems; Different product classes; Flow time; Simulation models; Correction terms.
Improving production systems with lean: A case study in a medium-sized manufacturer
by Sérgio Vieira, Rui Borges Lopes
Abstract: Lean principles and tools have been increasingly employed in companies across several sectors, with numerous successful implementations both inside and outside production environments. In the case of Portuguese companies, few works have reported the application and corresponding results of lean, and even fewer focusing on small and medium sized companies.
This work presents a case study of an implementation of several lean principles and tools in the production sector of a Portuguese medium-sized screw cap manufacturer. Visual management, A3 thinking, and single-minute exchange of die (SMED) were employed to identify and reduce inefficiencies and waste in the shop floor. The implementation of these principles and tools is detailed, showcasing the necessary adjustments for being correctly embedded in the companys culture. Qualitative and quantitative results are presented concerning the case study, where a continuous improvement culture was adhered to and a significant gain in productivity could be observed.
Keywords: Lean tools; case study; bottle cap industry.
MIP based heuristic algorithm for finite capacity MRP problem in hybrid flow shop with unrelated parallel machines.
by Watchara Songserm, Teeradej Wuttipornpun
Abstract: A main drawback of the material requirement planning system (MRP) is that it assumes fixed lead time, resulting in capacity problems recently called finite capacity MRP (FCMRP). This paper proposes a mixed integer programming (MIP) based heuristic algorithm that can solve the industrial scale FCMRP problem in hybrid flow shop with unrelated parallel machines. The heuristic is applied to construct an initial sequence of operations, whereas the MIP model is applied to determine the optimal machines and start times for the operations based on the initial sequence. The objective is to minimise the total cost, defined as the sum of tardiness, earliness, idle time, and work in process holding costs. Performances of the proposed algorithm are evaluated using real data from automotive industries. The result shows that the total cost of the proposed algorithm is substantially reduced, compared with the recent FCMRP algorithm (HGATS). Moreover, the required runtime is within a practical limit.
Keywords: Mixed integer programming; Finite capacity MRP; Hybrid flow shop; Unrelated parallel machines; Application in industry.
A Firefly Algorithm for the Heterogeneous Fixed Fleet VRP
by Panagiotis-Petros Matthopoulos, Stella Sofianopoulou
Abstract: Vehicle routing is a key success factor in logistics problems. A variation of Vehicle Routing problem (VRP), the heterogeneous fixed fleet VRP in which the vehicles available for distribution activities are characterized by different capacities and costs, is tackled. A hybrid firefly algorithm for optimizing the routing of heterogeneous fixed fleet of vehicles in logistics distribution systems is presented. The principles and key steps of the proposed firefly algorithm are introduced in detail. Experimental results from solving the heterogeneous fixed fleet vehicle routing problem when tested on benchmark datasets are demonstrated. Moreover, the algorithm is compared with other algorithms solving similar problems in order to prove the effectiveness of the proposed hybrid firefly algorithm.
Keywords: Firefly algorithm; Nature Inspired Metaheuristic Algorithms; Combinatorial optimization; Vehicle routing problemrn.
A reliable and computationally efficient model for professional gas boilers
by Emidio Tiberi, Riccardo Furlanetto, Daniele Turrin, Marzio Piller
Abstract: Gas boilers can be integrated into professional ovens for steamcooking
processes. Their heat-transfer efficiency depends on several parameters,
as exhaust gas temperature, combustion stability, fuel type, excess air.
Computational Fluid Dynamics (CFD henceforth) provides a viable option
to assess several digital prototypes of gas boilers under different operation
conditions. Short setup-time, low computational cost and close matching with
experimental results are key features of a CFD model suitable for the industrial
We propose a reliable and computationally-efficient CFD model for gas boilers,
operating under steady conditions. The model does not take explicitly into account
both combustion and water boiling.
The accuracy of the proposed model is confirmed by the excellent agreement
between experimental measurements of the exhaust gas temperatures and the
corresponding numerical results.
Keywords: gas boilers; CFD; heat transfer; experimental validation; computational efficiency.
Evaluating the Effectiveness of Spare Parts Replenishment Methods for Warranty Service Satisfaction
by Andrew H. Bluett, Hector A. Vergara, J. David Porter
Abstract: After a mobile communication device (MCD) has been sold, the customer may find that there is a defect. MCD manufacturers usually contract a third-party warranty service provider (WSP) to perform repairs of manufacturing defects and to ship a repaired MCD back to the customer. The contract established between the MCD manufacturer and the WSP clearly specifies the minimum required service levels for repair lead time and fill rate that must be met by the WSP. In this research, the ability of two distinct spare parts replenishment methods to meet minimum required service levels at a minimum cost was evaluated using a discrete event simulation approach. The results show that both methods satisfy minimum service level requirements with no significant difference in average total system cost. However, the results also indicate that their performance with respect to average repair lead time and average fill rate is significantly different.
Keywords: discrete event simulation; mobile communication device; spare parts replenishment; inventory management; replenishment planning; warranty service.
Optimal buffer allocation for serial production lines using heuristic search algorithms: A comparative study
by Leyla Demir, Alexandros C. Diamantidis, Deniz Türsel Eliiyi, Michael E. J. O'Kelly, Semra Tunali
Abstract: The buffer allocation problem (BAP) is one of the major optimization problems faced by production system designers. BAP is widely studied in the literature since buffers have a great impact on efficiency of production lines. This paper deals with buffer allocation problem and compares the performance of three heuristic search algorithms, namely myopic algorithm (MA), degraded ceiling (DC), and adaptive tabu search (ATS) with respect to both throughput maximization and also computational time. To generalize experimental findings the experiments have been conducted both for reliable and also unreliable serial production lines over various sizes of problem instances. It is hoped that the findings of this research study can serve as a guideline for the decision makers while designing and operating production lines.
Keywords: Production lines; Buffer allocation problem; Tabu search; Myopic algorithm; Degraded ceiling.
Sustainability Modeling of Health Information Exchanges in Dynamic Environments
by Abdulaziz Ahmed
Abstract: Healthcare practitioners have realized that sharing patient data is beneficial, which can be accomplished by joining a Healthcare Information Exchange (HIE) network. Many challenges confront those joining an HIE network, and one of the most serious is the networks financial sustainability. This paper develops three linear programming models to study the sustainability of an HIE network. Two types of agent are considered: the Healthcare Provider (HCP) and the HIE network owner. Model 1 aims to maximize the benefits for HCPs, while Models 2A and 2B are intended to maximize the benefits for HIE owners. The results of Model 1 showed that the benefits for HIE owners and HCPs were positive. In Models 2A and 2B, the benefits for HIE owners were sometimes negative because in some cases there were not enough joined HCPs. This study helps decision makers understand the sustainability of HIE networks in a dynamic environment.
Keywords: Healthcare information exchange; linear programming; optimization.
An Online Quality Monitoring Tool for Information Acquisition and Sharing in Manufacturing: Requirements and Solutions for the Steel Industry
by Satu Tamminen, Eija Ferreira, Henna Tiensuu, Heli Helaakoski, Vesa Kyllönen, Juha Jokisaari, Esa Puukko, Juha Röning
Abstract: The purpose of this study was to develop an innovative online supervisor system to assist the operators of an industrial manufacturing process in discovering new solutions for improving both the products and the manufacturing process itself. In this paper, we discuss the requirements and practical aspects of building such a system and demonstrate its use and functioning with different types of statistical modelling methods applied for quality monitoring in industrial applications. The two case studies presenting the development work were selected from the steel industry. One case study predicting the profile of a stainless steel strip tested the usability of the tool offline, while the other study predicting the risk of roughness of a steel strip had an online test period. User experiences from a test use period were collected with a system usability scale questionnaire.
Keywords: data mining; generalized boosted regression; GBM; quality improvement; online monitoring; knowledge representation; product design.
A Synergic Multivariate Statistical Process Control Framework for
Monitoring, Diagnosis, and Adjustment of Multiple Response Abrasive Machining Processes
by Sagar Sikdar, Indrajit Mukherjee, Subash C. Panja
Abstract: In various abrasive machining processes, output product quality is defined in terms of multiple critical characteristics (or responses) and their deviations from target values. These multiple characteristics or responses are often interacting or correlated. In such a situation, changing the process operating conditions for improving or controlling the quality of one response may deteriorate the quality of another. Thus, there is a need to simultaneously consider all responses and recommend a trade-off operating condition for process control and optimisation. Two important fields that consider simultaneous control and optimisation of multiple responses are the multi-variate statistical process control (MSPC) and multiple response optimisation (MRO). In the context of MSPC, there are three distinct phases of process control, namely, (i) correct identification of an out-of-control signal, (ii) identification of influential response variable(s) that contribute to an out-of-control signal, and finally (iii) re-establishment of the stability of the process by implementing necessary adjustments in the process setting conditions. Although various parametric and non-parametric MSPC and MRO solution approaches have been previously proposed, there is limited prior research work on the integration of the MSPC and MRO solution approaches to ensure the stability and process capability of the abrasive machining processes. In this study, a synergic MSPC and MRO approach is proposed, based on the Mahalanobis distance (MD), MahalanobisTaguchi system, r-control chart, seemingly unrelated regression (SUR) and non-linear optimisation technique, to ensure the stability and capability of the abrasive machining process. The suitability of the proposed approach is verified using a real life abrasive machining case data set.
Keywords: Abrasive Machining Process; Multivariate Statistical Process Control; Multiple Response Optimization; Mahalanobis-Taguchi System; r-control chart; Multivariate Process Capability.
Analytical evaluation of agile success factors influencing quality in Banking Sector
by Viral Gupta, Parmod Kumar Kapur, Deepak Kumar, Satya Prakash Singh
Abstract: Todays software applications deployed in an enterprise caters to the complex business processes, integrates various business units and addresses requirements of global customer base. The traditional methodology of software engineering succumbs towards the changing need of customer and technology advancement. Agile methodology targets complex systems with its iterative, incremental and evolutionary approach. There are numerous factors attributing towards the successful implementation of agile methodology. The measurement and evaluation of these agile success factors in an enterprise remains a challenge. This research paper presents a framework to analyse and measure the success factors of agile methodology in an enterprise, using Two-way assessment and Analytic hierarchy process (AHP). A case study has been conducted in a large enterprise in banking sector and twelve success factors of agile implementation have been evaluated and measured. The proposed framework makes significant contributions to the research community by providing improvement in the maturity of Agile implementation in an enterprise by 54%.
Keywords: Software Quality; Agile methodology; Two-way assessment; Analytic hierarchy process; Continuous integration; Enterprise application.
An Inventory System with Service Facility and Feedback Customers
by Amirthakodi M, Sivakumar B
Abstract: This article considers a single server queueing-inventory system with finite waiting room. The customers arrive according to a Poisson process. The individual customer's unit demand is satisfied after an exponential service time. After a customer is served, she will decide either to join the retrial group, which is of infinite orbit, for another service or leaves the system according to a Bernoulli trial. These orbiting customers compete for service according to constant retrial policy. The service time for these feedback customers are assumed to be exponential. The inventory is replenished according to an (s,S) policy and the lead times are exponential. We have carried out the busy period, waiting time and steady state analysis of the system. Some important system performance measures in the steady state are derived and the long-run total expected cost rate is also calculated. The results are illustrated numerically.
Keywords: (s,S)inventory policy; Finite Waiting Hall; Feedback customer; Constant retrial policy; Waiting time distribution.
An optimization framework of a global supply chain considering transfer pricing for a Colombian multinational company
by Juan Camilo Paz, John Wilmer Escobar
Abstract: This paper considers the problem of designing a global supply chain of consumer products by considering transfer pricing. It is based on a global established supply chain for which the central problem is to determine the closure and consolidation of national distribution centers. The problem has been solved by using a mixed integer linear programming model considering decisions regarding the location of facilities, transfer pricing, plant capacities, and the flow of products through the supply chain. The objective function of the proposed mathematical model is to maximize the total profit after tax by considering the determination of global revenues in the different facilities and their division over the chain. The mathematical model has been tested with real information obtained from a Colombian multinational company of the commercial sector. The obtained results confirm the efficiency of the proposed model by including transfer pricing and the positive impact on the determination of the profits of the case study company.
Keywords: Optimization of Global Supply Chains; Transfer Pricing; Tax; Logistics.
Risk control with options hedging for an oil import enterprise
by Yu Xing
Abstract: The paper examines the performance of several options hedging models, namely with currency options, with crude oil options and with both currency and crude oil options, for a crude oil importing firm. We simulate the returns, calculate optimal hedge ratios and suggest a risk management strategy. The empirical results show that the models of GJR-t and EGARCH-t are respectively suitable to forecast the volatilities for WTI crude oil price and exchange rates (CNY/USD). Student-t Copula is the best fitting function to describe the dependence structure among the bivariate return series. Furthermore, by comparing the risks measured by CVaR (Conditional Value at Risk), we suggest that the risk appetite investors can buy currency options for hedging and the risk aversion investors can buy crude oil options for hedging., it is not wise to buy both options of currency and crude oil in term of budget.
Keywords: Risk hedging; Optimization modeling; Simulation method; Conditional Value at Risk.
Building Sustainable Models and Assessments into Petroleum Companies: Theory and Application
by Ibrahim Garbie
Abstract: There is an urgent need to build a sustainable models to predict future in oil and gas sector to accommodate and respond to the short-term pressures. One of the main issues in petroleum companies is the concept of sustainability interpreted in a multitude of different ways. Numerous frameworks have been presented to assess sustainability, but there is no agreement on a common set of criteria for analysis, investigation, modeling and assessment. A framework of sustainability in oil and gas industry was built and investigated by two important levels: Micro-level and Macro-Level. The Micro-Level was proposed to evaluate sustainable index in single petroleum company and Macro-Level was suggested to assess sustainable index in the whole oil and gas sector. Practical indicators have been suggested and developed to assess sustainability indexes. An implementation of the suggested framework was applied through three big petroleum companies in Sultanate of Oman. The results shows that some companies had sustainable indices more than others.
Keywords: Oil and gas industry; sustainability; sustainable development.
A hybrid approach for modelling dynamic flows and systemic risks in supply chains
by Ke Sun, James Luxhøj
Abstract: The uncertainty of supply chain operations is becoming more complex with the growth of globalized business collaborations. Temporal business environment fluctuations cause disruptions that require quantitative risk analysis tools to understand and mitigate supply chain risks. This paper presents the formulation and application of the Dynamic Flow Bayesian Networks (DFBNs) and the Optimized Dynamic Flow Bayesian Networks (ODFBNs) for a three-stage supply chain. DFBNs are created by integrating Dynamic Bayesian Networks (DBNs) and System Dynamics (SD) to demonstrate the feedback flows of a supply chain with systemic risks considered. ODFBNs that incorporate mathematical optimization with the original DFBNs are also developed to generate an optimization-enhanced risk-influenced dynamic flow analysis. DFBN and ODFBN provide supply chain practitioners with a more effective reference for their business strategy. Comparison between the ODFBN and the DFBN is illustrated with a discussion of preliminary modelling results.
Keywords: supply chain; risk analysis; Dynamic Bayesian Networks; System Dynamics; multi-objective optimization; hybrid model.
Using social network analysis for industrial plant layout analysis in the context of Industry 4.0
by Leonilde Varela, Vijay Manupati, Suraj Panigrahi, Eric Costa, Goran Putnik
Abstract: Social network analysis (SNA) is a widely studied research topic, which has been increasingly applied for solving different kinds of problems, including industrial manufacturing ones. This paper focuses on the application of SNA on an industrial plant layout problem. The study aims at analysing the importance of using SNA techniques to study the important relations between entities in a manufacturing environment, such as jobs and resources in the context of industrial plant layout analysis. Here, performance measures such as maximum completion time of jobs (makespan), resource utilization, and throughput time have been considered to evaluate the system performance. Later, with the simulation analysis, the relationships between entities and their impact on the system performance is evaluated. The experimental results revealed that the proposed SNA approach supports to find the key machines of the systems that ultimately leads to the effective performance of the whole system. Finally, the identification of relations among these entities supported the establishment of an appropriate plant layout for producing the jobs in the context of Industry 4.0.
Keywords: Manufacturing systems; plant layout; social network analysis; case study.
An approach to assess robustness of reconfigurable manufacturing system
by Ateekh Ur Rehman
Abstract: A manufacturing system is considered, which produces thirty products using seventeen conventional machines and different process plans for each product. The system accepts customer orders for any combination of these products. These orders received from time to time may relate to different combinations of the products of varying quantities. The system is simulated using ProModel and the exercise helped in quantifying how the manufacturing system would perform under different scenarios characterized by the combinations of various operational features. The performance of the system is measured using performance measures such as machine utilization, through put time, product earliness, product lateness and product block time. Nine different alternative configurations were developed and simulated. Taguchi analysis led to some interesting inference, which appears to be extending good support to manufacturing system performance analysis. The details of the simulation model, analysis of the results and the inference drawn are presented in this paper.
Keywords: Performance evaluation; reconfiguration; simulation; ProModel; robustness; Signal to noise.
Fostering systematic eco-innovation in an Industrial symbiosis environment using DEMATEL
by Jayakrishna Kandasamy, Vimal KEK, Medha Vibha, Shubham Jain, Asela K. Kulatunga
Abstract: In todays rapidly changing and evolving world, manufacturing acts as one of the most important part for the development of any organization. This study is done in order to analyze the performance of any industry on the basis of opinions of industrial experts. Decision making trial and evaluation laboratory (DEMATEL) method has helped the industry to achieve benefits in business management by Eco-Innovation. Industrial Symbiosis helps different organizations to pool their resources, discuss their problems, their merits-demerits and also to share their profit. This study is mainly done in order to know about the different key points by experts who will enhance the performance of Industrial Symbiosis. These attribute can be used as the reference point to encourage the operational activity. This study collected information from sugar mill industry, paper mill and cement industry in Tamil Nadu, India. DEMATEL method is used to visualize the impact of different attributes on the company. It has wide range from very basic, such as to analyze the problem to finally getting the solution of problem. By using DEMATEL approach, proper graphs, data can be plotted which clearly shows the amount of effects each factors have on each other and on organization. Multi Criteria decision making (MCDM) also uses the DEMATEL properties in order to show interrelationship between different factors, to obtain a threshold value for further study.On the basis of DEMATEL approach Solid Waste Management(C3) with the largest R+C value=23.0 and Growth Rate=5.6396 as a smallest value are identified respectively. Company need to focus mostly on Solid waste management to in order to improve the efficiency in terms of eco-innovation and industrial symbiosis.
Keywords: Multiple attribute decision making; DEMATEL; Criteria interaction; sustainability; Eco-Innovation; Industrial Symbiosis.
Supply Chain Performance Measurement Systems: A Qualitative Review and Proposed Conceptual Framework
by Sharfuddin Ahmed Khan, Amin Chaabane, Fikri Dweiri
Abstract: MManagement of supply chain (SC) is becoming challenging by every passing day due to high competition, globalization, and digitalization because of the recent adoption of Internet of Things (IoT) technologies in order to increase supply chain visibility. Due to this fact, importance of supply chain performance measurement systems (SCPMS) has been increased significantly. To cope up with these challenges and remain competitive, organizations are keen to evaluate SC performance more precisely. Therefore, this paper adopts a qualitative review methodology to find out if existing SCPMS are in line with the current emerging technology trends of managing SC and measuring SC performance and if not, what will be the characteristics of future SCPMS. Results show particularly that existing SCPMSs are not adequate to cope up with the complexity and the technology advancement observed in Supply Chain Management as a smart way for measuring modern SC performance is needed. Finally, this study proposes a conceptual supply chain performance measurement (SCPM) framework to fill the identified research gaps.
Keywords: Supply Chain Management; Supply Chain Performance Measurement Systems; Knowledge Base System; Integrated Framework; Long-term Decision Criteria; Short-term Decision Criteria.
Adaptive Online Successive Constant Rebalanced Portfolio Based on Moving Window
by Jin'an He, Xingyu Yang, Hong Lin, Yong Zhang
Abstract: In the nonstationary financial market, considering earlier observations
may be little or irrelevant to the current investment decision-making, we design
two kinds of adaptive online portfolio strategies only based on recent historical
data. Firstly,we design an adaptive online portfolio strategy by linearly combining
the last portfolio and the best constant rebalanced portfolio corresponding to the
recent historical data, which we call moving window. We determine the length
of the moving window by adaptive learning. More precisely, we consider the
strategies that always adopt the best constant rebalanced portfolio corresponding
to the moving window of different fixed lengths as different experts, and at the
beginning of the current period, we choose the length ofmoving window the same
as the expert achieving maximum current cumulative return. Furthermore, we
determine the length ofmoving window by only using the recent historical data to
adaptively learn, and design another adaptive online portfolio strategy.We present
numerical analysis by using real stock data from the American and Chinese
markets, and the results illustrate that our strategies perform well, compared with
some benchmark strategies and existing online portfolio strategies.
Keywords: online portfolio selection; investment strategy; moving window; adaptive algorithm.
Supply Chain Coordination and Decision under Effort-Dependent Demand and Customer Balking Behavior
by Guangdong Liu, Tianjian Yang, Xuemei Zhang
Abstract: The paper explores supply chain coordination under a sales effort-dependent demand and customer balking scenario and analyzes the impacts of revenue- and cost-sharing contracts on the decisions of supply chain members. This paper subsequently develops a two-echelon supply chain consisting of one supplier and one retailer and examines two models that incorporate customer balking and sales efforts: in one model, the retailer offers a revenue sharing-only contract, and in the other model, the retailer and the supplier bargain on the revenue and cost-sharing contract. The results show that the revenue- and cost-sharing contract can coordinate the decentralized supply chain better than it can coordinate a centralized supply chain and that the effects of customer balking on the supply chain are clear; when customer balking occurs, the probability of a sale occurring can increase the profit of the supply chain, while the threshold of inventory and the sales effort can improve the marketing demand. In addition, a Pareto-improvement scenario and managerial decisions for supply chain coordination are derived from a numerical analysis.
Keywords: revenue- and cost-sharing contract; customer balking behavior; newsvendor model; Stackelberg game; effort-dependent demand.
Fleet Dimensioning and Scheduling in the Brazilian Ethanol Industry: A Fuzzy Logic Approach
by Henrique Ewbank, Peter Wanke, Henrique L. Correa
Abstract: This work solves a real-world multi-depot vehicle routing problem (MDVRP) with a homogeneous fleet and capacitated depots. A pipeline company wants to establish a vehicle policy in order to own part of its fleet and serve its customers for a period of 1 year. The company also wants to know the schedule of the visits for collecting ethanol from 261 producers and taking it to their three terminals located in Brazil. This problem presents uncertain demand, since weather conditions impact the final crop and uncertain depot capacity. Due to the vagueness of managers speech, this problem also presents uncertain travel time. Authors use fuzzy logic to model uncertainty and vagueness and to split the initial instance into smaller ones. Besides solving a real-world problem with fuzzy demand, fuzzy depot capacity and fuzzy travel time, this paper contributes with a decision making tool that reports different solutions for different uncertainty levels.
Keywords: multi-depot vehicle routing problem; fuzzy logic; job scheduling; real-world problem; expert system.
Innovation in ergonomics: a survey in the agribusiness sector of Brazil
by Raquel Kraemer Sabadin, Eliana Andréa Severo, Julio Cesar Ferro De Guimarães
Abstract: The healthy organisation corroborates participatory environments, innovative, centralised in the sense of human relations in the workplace, anthropocentric essence of ergonomics. The aim of this study is to analyse the relationship between innovations in ergonomics, absenteeism and in the risk of lifting loads in six units of an agribusiness. The method we used was a quantitative survey of a descriptive nature, survey type with a sample of 419 workers, which were used measures that explored the relationship between the study variables, through factor analysis and multiple linear regression. The results show that the workplace environment explains 46% the occurrence of process and organisational innovations in ergonomics, since the process and organisational innovations in ergonomics justify by 40% the significant reduction of absenteeism. Organisations have in its management processes the involvement of workers and make innovations that refine their performance and contribute to the human relationship in the workplace, which positively affect both, the organisation and the worker.
Keywords: Process Innovation; Organisational Innovation; Ergonomics; Absenteeism; Agribusiness; Brazil.
A General Variable Neighborhood Search for Multi-Skill Resource-Constrained Project Scheduling Problem with Step-Deterioration
by Huafeng Dai, Wenming Cheng, Wucheng Yang, Yupu Wang
Abstract: This paper proposes a general variable neighborhood search approach (GVNS) for solving the multi-skill resource constrained project scheduling problem (MS-RCPSP) under step-deterioration aiming to minimize maximum completion time. To assess the performance of the proposed GVNS, integrating five neighborhood structures and a disturbance step, computational experiments are carried out on two sets instances. One group takes no account of deterioration where the proposed GVNS achieved highly performance compared with the state-of-the-art algorithms in the literature, and the other group of experiments on modified dataset considering the step-deterioration effect also demonstrates the capability of the GVNS to find high quality solutions.
Keywords: deterioration effect; multi-skill; resource constrained project scheduling problem; general variable neighborhood search.
OPTIMAL MULTIVARIATE CONTROL CHARTS BASED ON LINEAR COMBINATION OF NORMAL VARIABLES
by Sandra García, Andres Plaza, Joseph León
Abstract: In some productive processes where normal variables intervene, it is necessary to control specific directions of shifts (increments or decrements) in the mean vector. Many multivariate control charts base their statistics on quadratic forms and do not rapidly detect a shift in a specific direction. In this paper, we propose two charts based on the linear combination of correlated normal variables, the LCN (Linear Combination of Normal Variables) and LCPC (Linear Combination of Principal Components). These charts were designed to detect a specific shift in the process. To analyse the performances of these charts, we have developed a friendly program that finds the best parameters through Genetic Algorithms. This algorithm minimises the out-of-control ARL (Average Run Length) for a proposed shift in the mean vector under the restriction of a desired in-control ARL value. The proposed control charts are Shewhart type, which show better performances than the Hotelling T2 chart.
Keywords: Control Chart; the Hotelling T2 control chart; Optimization; Principal Components; Normal Variables; Genetic Algorithm; Heuristic; Average Run Length; One-Sided Chart; Shewhart chart.
Back-projection Imaging Algorithm of Random Noise Frequency Modulation Continuous Wave SAR
by Xu Xingjian, Yuehua Li, Can Wang
Abstract: The combination of random noise frequency-modulation continuous wave technology and synthetic aperture radar(SAR) promises a cost-effective, low probability of intercept and high electromagnetic compatibility. This paper analyzes the time-domain restricting algorithms for random noise frequency modulation continuous wave (RNFMCW) SAR. Two versions of the back-projection algorithm are proposed. At first, the radar antenna continuous motion in a pulse repetition period of RNFMCW SAR is analyzed. Then the phase term which is caused by the continuous motion is described by a approximate expression with Taylor expansion. Meanwhile, both the start-stop approximate back-projection algorithm and the modified back-projection algorithm are proposed. In the end, with the help of numerical simulation, the limitations of the start-stop approximation back-projection algorithm and the validity of the modified back-projection algorithms are illustrated.
Keywords: random noise; FMCW; SAR; back-projection; Taylor expansion; correlation.
Comparison of AHP-TOPSIS and AHP-AHP Methods in Multi-Criteria Decision Making Problems
by Deepak Sharma, Srinivasan Sridhar, David Claudio
Abstract: Decision making is a highly researched topic and various methods have been developed to facilitate a decision maker in choosing the best alternative. Saatys Analytic Hierarchy Process (AHP) has been very popular since 1977 and has been adapted all over the world. However, AHP is a highly-debated topic. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is another Multi-Criteria Decision-Making (MCDM) method developed by Hwang and Yoon in 1981 as a ranking method. This research is focused on identifying which is the MCDM method between AHP and TOPSIS. Since TOPSIS is a ranking method, the authors propose to combine AHP and TOPSIS methods and determine which methods ranking (AHP, AHP-TOPSIS combination, and TOPSIS with equal weights) aligns more closely with the DMs initial preference. Moreover, this research states the efficiency of the method by comparing the time it takes to make a decision and its reliability.
Keywords: AHP; AHP-TOPSIS; Decision Maker Initial Ranking; Multi-Criteria Decision Making.
Performance Modelling and Optimization of the Rice Processing Industrial System using PSO
by Ajay Kumar
Abstract: The present work includes the performance modelling and optimisation of the rice processing Industry for achieving the maximum availability. The study presents a methodology for availability evaluation of the process industry. For the increased production rate and resource utilization, the maintenance plan should be developed which can predict the effect of performance parameters with time. The performance modelling for the Steady State Availability (SSA) has been done using Markov method using historical failure and repair database followed by the system optimization using Particle Swarm Optimization (PSO). The performance parameters are assumed to be negative exponential which are independent to each other and repaired units are considered as fine as original. The uncertainties of failure and repair rates (FRR) are removed by selecting these parameters randomly in PSO. The maximum availability of each system for all possible combinations of FRR within fixed minimum and maximum limits for each subsystem has also been computed. The rice processing plant consists of several subsystems for which optimum availability level for rice processing plant for random combinations of FRR has been found. The computed results are economically beneficial for the plant personnel in improving the production rate and maintenance planning.
Keywords: Performance modelling; Rice processing plant; Markov Modelling; Particle Swarm Optimization; Selection; Decision Support System.
Simulated Annealing Approach to Minimize Total Weighted Tardiness of Non-Identical Parallel Batch Processing Machines
by Rajani Kakkunuri, Christine Nguyen, Purushothaman Damodaran
Abstract: A variety of industries use Batch Processing Machines (BPMs) that can process multiple jobs simultaneously per machine. This research considers the scheduling of multiple jobs onto non-identical parallel BPMs while minimizing the total weighted tardiness. The problem under study is NP-hard and solving it to optimality using a commercial solver requires long run times when the size of the problem increases. A Simulated Annealing (SA) approach is proposed to find good solutions for large problem instances within short run times. The results obtained are compared to two metaheuristics, Particle Swarm Optimization (PSO) and Differential Evolution (DE), proposed in the literature and a commercial solver (CPLEX). An experimental study is conducted to evaluate the different solution approaches on a set of problem instances. Based on results, the authors conclude that SA is highly effective in solving large problem instances within reasonable run times when compared to CPLEX, PSO and DE.
Keywords: Scheduling; batch processing machines; weighted tardiness; simulated annealing.
The value of fleet information: A cost-benefit model
by Sini-Kaisu Kinnunen, Salla Marttonen-Arola, Timo Kärri
Abstract: Internet of Things (IoT) technologies enable the collection of wide-ranging data related to industrial assets which can be used as a support of decision making in asset management, varying from operative maintenance decisions concerning one asset to the management of asset fleets. Technologies and data-refining processes need to be invested in to create knowledge from the massive amounts of data. However, it is not clear that the investments in technologies will pay back, as the data analysis and modelling processes need to be developed as well, and the potential benefits must be considerable. This paper contributes to this field by modelling the costs and benefits of IoT investments. As a result, we develop a model that evaluates the value of fleet information in the maintenance context by applying the cost-benefit approach. The costs consist of hardware, software and data processing -related work costs, while the benefits comprise savings in maintenance and quality costs, as well as other savings or increased revenues. Testing the model with a descriptive case demonstrates that the realized cost savings and other benefits need to be considerable for the investment in IoT technologies to be profitable. The results emphasize the importance of data utilization in decision making in order to gain benefits and to create value from data.
Keywords: fleet; cost-benefit; asset management; investment appraisal; maintenance; life-cycle analysis; Weibull; life-cycle data; cost savings; value of information.
Meta-heuristics for Dynamic Real Time Scheduling of Diffusion Furnace in Semiconductor Manufacturing Industry
by M. Vimala Rani, M. Mathirajan
Abstract: It is observed from the literature that most of the earlier research in dynamic scheduling of diffusion furnace (DF) in Semiconductor Manufacturing industry, considers only future arrival of jobs. However, in reality along with the future arrival of jobs, various unexpected real time events related to jobs, and/or resources will occur. Hence, this study addresses the important real life characteristics of considering simultaneously both future arrival jobs and the occurrence of a job and/or resource related real time events while scheduling DF, called as dynamic real time scheduling (DRTS), with the scheduling objective of minimizing total weighted tardiness (TWT). This study first explains the mathematical model for dynamic scheduling of single diffusion furnace to minimize TWT. Since the research problem that is considered in this study is shown to be NP-hard, this study proposes meta-heuristics: Simulated Annealing (SA) and Tabu Search (TS) for DRTS of DF. In this study, for both SA and TS, six different initial solutions obtained from six variants of greedy heuristic algorithm (GHA) are given as input to improve the solution and this would result 12 variants of meta-heuristics (six variants of SA and six variants of TS). To find the most performing variants among the proposed 12 variants of the meta-heuristics, a series of computational experiments are conducted by empirically comparing the effectiveness with (a) best solution among the proposed 12 variants of the meta-heuristics, and (b) estimated optimal solution. In addition, the results obtained from the empirical analyses are further verified through two different statistical analyses. From empirical and statistical analyses on 270 problem instances, one of the proposed versions of the SA algorithm outperforms in comparison with the other proposed variants of the meta-heuristics.
Keywords: Simulated Annealing; Tabu Search; Greedy Heuristic Algorithm; Real Time Events; Dynamic Real Time Scheduling; Diffusion Furnace.
An Inventory Positioning Model under Vendor Managed Inventory System
by Jayalal Wettasinghe, Huynh Trung Luong
Abstract: Inventory management is one of the key functions in any supply chain. Since inventory cost occupies a significant portion of supply chain cost, it is essential to employ a good inventory policy in order to reduce the supply chain cost while improving the service level. This paper presents a vendor managed inventory (VMI) policy with emergency orders for a supply chain with a single vendor and two independent retailers. A mathematical model is developed using the concept of demand rate, assuming Poisson demand for the retailers. The formulated model is used to help determine the optimal system base stock level, delivery quantities to retailers and the cycle length such that the total expected inventory cost of the system is minimised. Numerical experiments and sensitivity analysis are then conducted to examine the effect of model parameters on total inventory cost and optimal solution.
Keywords: Vendor managed inventory; Emergency orders; Inventory management; Optimal base stock level.
Analysis of an M[X]/G(a, b)/1 queueing model with multiple vacation controllable arrival during multiple vacation and two phases of repair with delay
by T. Deepa, AYYAPPAN Govindan
Abstract: The objective of this paper is to analyse anM[X]/G(a; b)/1 queueing model with multiple vacation, controllable arrival during multiple vacation and two phases of repair with delay. Whenever the queue size is less than 'a', the server resumes multiple vacation and continues this until at least 'a' customers are waiting in the queue. After finishing a batch of service, if the server is breakdown with probability ?, the server will be sent for repair after a short interval of time called delay time. After this delay, two consecutive phases of repair (first phase repair, second phase repair) are considered. After the second phase of repair or when there is no breakdown with probability 1-?, the server starts a vacation if the queue length is less than 'a'. Otherwise, the server starts a service under the general bulk service rule. Using supplementary variable technique, the probability generating function of the queue size at an arbitrary time is obtained for the steady-state case. Also some performance measures and cost model are derived. Numerical illustrations are presented to visualise the effect of various system parameters.
Keywords: Bulk queue; Controllable arrival; Multiple vacation; Two phases of repair; Delay time to repair.
Simulation of incompressible flows in channels containing fluid and porous regions
by Pavel Bulat, Konstantin Volkov
Abstract: Flows and heat transfer in channels containing both fluid and porous regions play an important role in various engineering applications. A better understanding of fundamental mechanisms in the fluid flows in porous regions are required in order to design and optimise gas bearings, air filters, and thermal insulation in the specific applications. Darcy-Brinkman-Forchheimer model is used to describe the flow inside the porous domain. The finite volume method is applied to solve these equations in a porous and open domain. The capabilities of the mathematical model and computational algorithm are demonstrated using test cases from various areas of practical applications. The effect of various physical quantities on velocity and pressure distributions is studied. The results of the numerical simulation of flows in porous domains are presented. The results obtained are in a good agreement with the experimental and numerical data available in the literature.
Keywords: porous medium; computational fluid dynamics; channel flow; fluid injection; gas bearing.
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.
Generalized Fault Detection and Correction Modeling Framework for Multi Release of Software
by Avinash K. Shrivastava, Iqra Saraf, Javaid Iqbal
Abstract: The intense competition in the technology around the world has forced the software firms to speed-up their software upgrades. This arises challenges as the reconsideration in code may add new bugs/faults or the undetected leftover faults from previous release may create complications in getting the software updated. Due to added complexity, the testing team may be unable to correct the fault upon detection leaving the actual fault to reside in the software, termed as imperfect debugging or there may be addition of extra fault during correction process, known as error/fault generation. Also, change in testing strategies and resources at any time point may result in change in fault detection and correction rate which is known as change point. Keeping these issues under consideration, we propose, an NHPP-based general framework for multi-release, two stage fault detection and correction software reliability models under imperfect debugging, error generation and change-point. Proposed model is validated on real life data.
Keywords: Non-Homogenous Poisson Process (NHPP); Software Reliability Growth Model (SRGM); Detection; Correction; Modeling; Imperfect Debugging; Change-Point; Multi release; Ranking; Distance Based approach(DBA.
Operational strategies for managing container terminals. An approach based on closed queueing networks.
by Iñigo L. Ansorena
Abstract: The port performance can be improved by a well-defined operations plan. We present a closed Jackson network (CJN) approach to analyse port operations from vessel to yard. The tool is not only focused on the berthing line, but also on the service level at the storage yard. It aims to determine the best way to operate a containership using two crucial parameters: container stowage and truck traffic. Thus, the CJN model determines the impact of cargo stowage on port performance (1)) and the impact of traffic on port performance (2)). Both are crucial to set the best strategy and ensure the efficient use of handling equipments. The CJN model is flexible in the sense that managers may plan different scenarios. The study suggests that terminal operators can achieve substantial benefits by means of the best resource allocation in each scenario.
Keywords: Jackson network; resource allocation; container terminals; operations management; port performance; trucks; traffic; bay plans; service rate; berth productivity; yard productivity; queues; matlab.
A fuzzy multi-objective model for a cellular manufacturing system with layout designing in a dynamic condition
by Ali Mohtashami, Alireza Alinezhad
Abstract: Cellular manufacturing system (CMS) plays a remarkably significant role in modern production systems. This paper presents a novel and practical fuzzy multi-objective mathematical model for a CMS in a dynamic condition considering the flexibility in allocating machines. The proposed model seeks to determine the best layout design in each production period. Two conflicting objectives are considered including minimizing the cost of manufacturing system due to the amount of production loss caused by waste, as well as minimizing the variance of fuzzy costs. Due to the complexity of the problem, non-dominate sorting genetic algorithm-II and multi-objective particle swarm optimization algorithm are designed to solve the model and to obtain the effective solutions. In order to demonstrate the efficiency of the algorithms and to choose the premier algorithm, both algorithms are evaluated in several random problems and then compared based on the existing measurement indicators. Then, the algorithms are tuned to solve the problem, based on which their performances are analyzed statistically. The applicability of the proposed approach and the solution methodologies are demonstrated as well.
Keywords: Cellular manufacturing system; fuzzy theory; NSGA-II algorithm; MOPSO algorithm.
Mathematical Modeling for Prediction of Tube Hydroforming Process using RSM and ANN
by P. VENKATESHWAR REDDY, B. VEERABHADRA REDDY, P. Janaki Ramulu
Abstract: Tube hydroforming (THF) is a special manufacturing process used to produce tubular components having applications in aerospace and automotive industries. The present study investigates the effect of process parameters such as coefficient of friction (CF), corner radius (CR) of the die and the axial feeding (AF) of the punch. The bulge ratio and thinning ratio has been evaluated to minimise the defects like bursting, wrinkling and buckling in the tubes. Apart from many parameters, these parameters are chosen to know the effect of each individual parameter on the outcomes namely bulge ratio and thinning ratio. Each factor has varied with three levels and a total of 27 simulations were carried out based on full factorial design. RSM and ANN were applied on the obtained results in order to predict the process parameters effect on the tube hydroforming process. The R-square value of ANN (0.9524 and 0.9517) is much closure to 1 when compared to R-square value of RSM (0.9539 and 0.9509).
Keywords: Tube hydroforming; FEM; RSM; ANN; MATHEMATICAL MODELLING.
Effects of proof tests on the safety performance of safety-instrumented systems
by Asklou Noureddine, Noureddine Rachid
Abstract: The imperfection in the values of the average probability of failure on demand (PFDavg) creates uncertainty about the effectiveness of safety-instrumented system (SIS). To overcome this problem, many parameters such as dangerous failures, common cause failures, diagnostic coverage rate and proof tests are taken into consideration. In order to emphasise the importance of the proof tests and show their effects on the safety performance of the SIS, a new analytical formula is developed in this study. The impact of these tests on the SIS's allocation of the safe integrity level (SIL) is shown through the results obtained in the present research.
Keywords: Safety-instrumented system; proof test; average probability of failure on demand; safety integrity level.
Throughput Time Reduction for Transportation of Foodgrains in Public Distribution System: A Value Analysis Approach
by K. Mathiyazhagan, Ajay Bohtan, Prem Vrat
Abstract: Food security to the population of India is ensured by the public distribution system (PDS) which involves an enormous and complex supply chain, wherein after procurement from the farmers foodgrains are distributed to the intended beneficiaries. This paper has analysed the large through put time in a sector of the supply chain using value chain analysis approach which has led to re-appropriation of the flow by minimising the time taken by non-value adding activities thereby increasing the efficiency of the supply chain. Reduction in this throughput time would lead to various advantages including the reduction in cost of the supply chain. Further, the model so arrived at could be reworked to bring a similar reduction in the throughput time at the macro level of the entire PDS supply chain.
Keywords: Supply Chain Management; Public Distribution System; Value Addition; Value Analysis; Throughput time.
A Responsive Multiplicative Holt-Winters (RMHW) Approach for Enhanced Forecasting Accuracy
by H. M. E. Kays, A. N. M. Karim, Mohd Radzi C. Daud
Abstract: In the competitive world of todays business, the quest for a reliable forecasting method to predict the future events is an ongoing process. Accordingly, efforts are being made incessantly to come up with ideas of superior forecasting techniques. As a classical and reliable forecasting technique of Operations Research, the Conventional Multiplicative Holt-Winters (CMHW) approach has been widely adopted for the time series events having seasonal and other causal variations. To make a forecast, the CMHW approach incorporates three different recursion processes for updating and estimating the level, growth rate and seasonal patterns of the associated time series. A set of estimated initial values having the number of elements equivalent to the seasonal length is used to initiate the recursion process for the seasonal parameter. Whereas, the recursion processes of level and growth rate are initiated by using the individual single stationary values. However, dependency on the stationary single initial values reflecting a strong adherence to the preceding patterns of a data set might compromise the forecasting accuracy and responsiveness. While, modification of the CMHW approach by facilitating the periodic updates of initial values in the recursion process of level and growth rate is presumed to have positive effect in reducing the forecast error. In this context a Responsive Multiplicative Holt-Winters (RMHW) forecasting approach is proposed and presented in this paper for which the conventional recursion process of level and growth rate are adjusted dynamically by accommodating a periodic updating procedure. The proposed forecasting method is tested for validation through several sets of data collected from real-life industry and case studies extracted from literature. Interestingly, for all the cases the forecasting accuracy is found to be enhanced by applying the proposed RMHW approach.
Keywords: Seasonal patterns; Demand forecasting; Smoothing constants; Multiplicative Holt-Winters Method; Forecasting Accuracy.
Considering pricing and uncertainty in design of a reverse logistics network
by Mohsen Zamani, Mahdi Abolghasemi, Seyed Mohammad Seyed Hosseini, Mir Saman Pishvaee
Abstract: Companies try to maximize their profits by recovering returned products of highly uncertain quality and quantity. In this paper, a reverse logistics network for an Original Equipment Manufacturer (OEM) is presented. Returned products are selected for remanufacturing or scrapping, based on their quality and proportional prices are offered to customers. A Mixed Integer Non-linear Programming (MINLP) model is proposed to determine the location of collection centers, the optimum price of returned products and the sorting policy. The risk in the objective function is measured using the Conditional Value at Risk (CVaR) metric. CVaR measures the risk of an investment in a conservative way by considering the maximum lost. The results are analyzed for various values of the risk parameters (α, and λ). These parameters indicate that considering risk affects prices, the classification of returned products, the location of collection centers and, consequently, the objective function. The model performs more conservatively when the weight of the CVaR part (λ) and the value of the confidence level α are increased. The results show that better profits are obtained when we take CVaR into account.
Keywords: Reverse logistics; Network design; Pricing; Risk.
Using GRASP Approach and Path Relinking to Minimize Total Number of Tardy Jobs on a Single Batch Processing Machine
by Purushothaman Damodaran, Panteha Alipour, Christine Nguyen
Abstract: This paper considers scheduling a single batch processing machine such that the total number of tardy jobs is minimised. The machine can simultaneously process several jobs as a batch as long as the machine capacity is not violated. The batch processing time is equal to the largest processing time among those jobs in the batch. As the problem under study is NP-hard solving a mathematical formulation optimality is computationally intensive. A greedy randomised adaptive search procedure (GRASP) is proposed with the assumption of arbitrary job sizes, arbitrary processing times and arbitrary due dates. A novel construction phase for the GRASP approach is proposed to improve the solution quality. In addition, a path relinking procedure is proposed for solving large-sized problems effectively. The performance of the proposed GRASP approach is evaluated by comparing its results to a commercial solver and a construction heuristic. Experimental studies suggest that GRASP is superior compared to the commercial solver and the construction heuristic.
Keywords: Minimizing total number of tardy jobs; batch processing machine; scheduling; GRASP; path relinking.
Use of Industrial Robots in Developing Countrys Scenario; Evidence from Three Dimensional Wireframe Graphs of Production
by Ejaz Gul
Abstract: Globally, use of industrial robots increased by 60% in last decade. In case of developing country, use of industrial robots is a bit tricky. This paper presents a functional model to explain use of robots and productivity link for industrial environment of developing country. Presented model is based on three scenarios; human solo (existing), robot solo (substitute) and combination of human and robots (complement). Taking production P as dependent variable, we determined its mathematical value for three scenarios. After detailed analysis with a help of latest software GeoGebra and 3D wireframe graphs, we concluded that in human solo scenario, factory production remain low in short run but increases in the long run; in robot solo scenario (substitute), production increases in the short run but decreases in the long run more than human solo scenario; while production increases in short and long run when robots are used mixed with human effort.
Keywords: Robot; human; solo; substitute; complement; industry; production; short run; long run; increase; decrease.
Influence of Demographic Factors on Productivity: A study among employees with different personality types in architectural firms
by Sriram K. V, Zara Poursafar, Lewlyn L. R. Rodrigues, Mohammad Haghighatpanah
Abstract: Though productivity of an organisation is influenced by many factors like skill set, wages, qualification, etc. personality trait of an employee is an important contributor. The present research attempts to identify the significance of relationship between the demographic factors of the employees and the productivity in the office of architects with and without the consideration of personality traits of employees. The survey for the study was carried out in 80 architects' offices located in Iran and India. The data was collected through a self-administered survey questionnaire using random sampling method on the basis of representative sampling. Statistical analysis was carried out using SPSS ver. 20. Chi-square test was used to test association between demographic factors and productivity. The study shows that there is a significant influence of demographic factors on employees' productivity while taking into consideration the different personality types.
Keywords: Demographic factors; Productivity; Personality types; MBTI; Psychology; Architects offices.
The discrete analysis of relay-races
by Eugene Larkin, Alexander Privalov
Abstract: It is shown that relay-races as a form of concurrency, are widespread in such fields of human activity, as industry, defence, economics, politics, etc. The analytical description of J stages relay-races, in which participate M teams, is considered. The model based on the semi-Markov process theory allows investigating a process evolution in detail but is of little use for computer calculation of forfeit, which the winner team receives from loser teams. To adapt analytical description to computer calculations, the method based on sampling of continual time densities of passing stages is proposed. Due to the method, initial semi-Markov process is converted to semi-Markov process with degenerative distributions, and the task of forfeit calculation is reduced to the task of rigid schedules effectiveness analysis, in which schedules are selected stochastically from the densities samples. Formulae for the stochastic summation of forfeits, is obtained. The results may be used for optimal planning the activity of participant teams when passing the distance.
Keywords: relay-race; rigid schedule; semi-Markov process; degenerative distribution; evolution; distributed forfeit; recurrent procedure.
Variable sample size control chart for monitoring process capability index Cpm
by Dja Shin Wang
Abstract: Abstract: Process capability indices (PCIs) provide numerical measures of process reproduction capability and are effective tools for quality assurance. In the present paper, we develop a variable sample size control chart, namely VSSCpm , to monitor PCIs for industry manufacturing to improve product quality. We set up the control limits; determine the upper and lower warning limits, fixed sample size, central region sample size, and warning region sample size for the control chart; and apply them to monitor PCICpm. We also use the average run length (ARL) as a monitoring performance indicator. To increase the in-plant applicability of the proposed method, we tabulate the performance value of the ARL for various commonly used situations. We perform a sensitivity analysis to study the effects of model parameters on the monitoring performance and then present an example to illustrate the proposed procedure.
Keywords: Key words: Process capability index; Variable sample size control chart; Quality monitoring performance.
Channel Coordination under Predictive and Corrective Maintenance Outsourcing
by Yu-Chung Tsao, Arke Li, Vu-Thuy Linh, Zhang Qinhong, Lu-Wen Liao
Abstract: With respect to Industry 4.0, predictive maintenance plays an important role in production systems. A better predictive maintenance strategy is absolutely essential to an efficient, reliable and safe production process. This study considers a supply chain that consists of a manufacturer and an external contractor wherein the manufacturer is willing to outsource the predictive maintenance activities provided by the contractor. In order to achieve channel coordination, we introduce three incentive contracts: 1) maintenance cost subsidisation contract; 2) uptime target and bonus contract; 3) uptime reward contract, which enhance the cooperation willingness of the contractor and increases profit for both parties, thereby leading to a win-win situation. We also discuss the feasibility of the contracts given improvements in the failure rate and maintenance capability. Theoretical results show that the uptime target and bonus and uptime reward contracts can achieve channel coordination under specific conditions given increases in the failures rate and maintenance capacity. Numerical results are further presented to reveal the managerial insights.
Keywords: predictive maintenance; corrective maintenance; maintenance outsourcing; channel coordination; contract design.
Bibliometric Research Indicators for Green Supply Chain Modeling
by Mohammed Alkahtani, Shafiq Ahmad, Mohammed A. Noman, Husam Kaid, Ahmed Badwelan
Abstract: Bibliometric research is a statistical technique that analyses written publications like articles, reviews, or books from a quantitative perspective. This study provides an overall picture of the research in green supply chain modelling (GSCM) sciences. This paper proposes a methodology. First, the articles have been collected using Web of Science based on selected keywords from 1995 to 2018. Next, the most influential journals, articles, keywords, authors, and institutions have been determined in GSCM. Then, the country analysis has been performed to analyse GSCM studies with respect to its geographical distribution. Finally, the VOS viewer software has been used to visualise the bibliographic material through co-authorship, co-occurrence, citation, bibliographic coupling, and co-citation analysis. The indicators identify the fundamental research in this field. It can be concluded that there is a high level of scattering in this field, with several effective nations, such as the USA.
Keywords: Bibliometric; Green supply chain modeling; Sustainability.
A Multi-Objective Scheduling Payment Pattern for Project Cash Flow by Considering Resource Constraints (A case study in power transfer system)
by Reza Kamranrad, Yaser Vahedi Geshniani, Iman Emami
Abstract: Financial aspects in project scheduling are specified by incoming and outgoing cash flows associated with events of the projects. As in the real world the project stakeholders are looking for benefit, here we have maximised project net value which is obtained from cost fraction of income. In fact, taking into account the objective function is it attempted that problem under study be closer to real-world issues. In this study, a mathematical model to maximise contractor net present value on the basis of payment pattern and consideration of resource constraint are presented. Since this issue is considered as NP-hard problems, to solve this, meta-heuristic multi-objective algorithms including NSGA-II, MOPSO and MOSA have been used. Finally payment patterns and an appropriate model are proposed to reduce the completion time and maximise the net present value of the project.
Keywords: Project scheduling; payment patterns; meta-heuristic algorithms; comparison of payment patterns.
Forecasting the International Air Passengers of Iran Using an Artificial Neural Network
by Sadoullah Ebrahimnejad, Farzin Nourzadeh, Kaveh Khalili-Damghani, Ashkan Hafezalkotob
Abstract: Forecasting passenger demand is generally viewed as the most crucial function of airline management. In order to organise the entering air passengers to Iran, in this study, number of international air passengers of Iran in 2020 has been forecasted using an artificial neural network. For this purpose, first, countries that have a similar status to Iran on some indicators, have been recognised by using 11 indices. Afterward, number of their air passengers has been forecasted by using the various training algorithms. Then, number of international passengers of Iran has been forecasted using the weighted average and similarity percentage of other countries in defined indices. It should be noted that training algorithm for countries have been chosen based on experimental error and the prediction accuracy has been set at 99% of confidence interval. Comparison of the results obtained from present study and other studies shows high accuracy of the proposed approach.
Keywords: Forecasting; Artificial Neural Network Algorithm; Air Transportation System; Time series; Training Algorithm.
Order Quantity allocation for Total inventory cost optimization to selected suppliers through VIKOR Technique
by ADAM NAGA PHANEENDRA, V. Diwakar Reddy, G. Sankaraiah
Abstract: In modern era, no. of potential suppliers for the industries are considerably increased and minimisation of total inventory cost becomes complicated. In response to the concern, we present and address the problem in two stages which efficiently assists to figure out the best suppliers among many and allocates order quantity to each supplier so as to mitigate overall inventory cost. Firstly, potential suppliers are listed and quantitative, qualitative data are collected based on opinion and judgemental survey. The normalised data is represented in square matrix and ranking is awarded to suppliers using utility measures and regret measures. Secondly, the fitness function is formulated and necessary constraints that primarily influences objective function is framed as nonlinear programming model. Further, the model is solved using LINDO software for its optimal solutions. The results show that the model considerably reduces total cost function as no. of orders from customer's increases.
Keywords: order quantity; Inventory management; supplier selection; VIKOR method.
Simultaneous Supplier Selection and Network Configuration for Green Closed-Loop Supply Chain under Uncertainty
by Mohammad Yavari, Mohaddese Geraeli, Mohammad Aftabsavar
Abstract: The current study integrates two strategic decisions, network configuration and selecting suppliers, for the green closed-loop supply chain under uncertainty. The demand and the rate of return are uncertain parameters. A robust multi-objective mixed-integer linear programming model is projected for the problem. The multi-period and multi-product model seeks to configure the network along with selecting suppliers and determining the type of technology used by manufacturers and recovery centres. The objectives include minimising the cost, minimising CO2 emission and maximising the weight of the suppliers. A two-stage model is utilised to solve the problem. The performance of the two-stage robust model is investigated in several numerical examples. The results revealed that the robust model compared to the deterministic model has better quality and is more reliable. Moreover, with a small additional cost, imposed by the robust model to face uncertainty, the robust model decreases the CO2 emission and has no infeasibilities.
Keywords: Green closed-loop supply chain; Supplier selection; Network configuration; Uncertainty; Robust optimization.
SCHEDULING OF AUTOMATED GUIDED VEHICLES AND MACHINES IN FLEXIBLE MANUFACTURING SYSTEMS: A SIMULATION STUDY
by Essam Kaoud, Mohamed El-Sebaie, Mahmoud El-Sharief, Mahmoud Heshmat
Abstract: Flexible manufacturing systems (FMSs) have widely expanded in industry sectors all over the world. Scheduling is one of the problems that face the life cycle of FMSs. This paper introduces the simultaneous scheduling problem of automated guided vehicles (AGVs) and machines in FMSs. The study is based on discrete event simulation (DES) to solve that problem using benchmark data used by previous studies. The objective of this study is to determine the starting and completion times of each job to minimise the makespan. The results validate the robustness of the simulation model, especially for large-scale problems. Furthermore, they are compared against the other approaches and show consistency.
Keywords: FMSs; AGVs; Scheduling; Simulation.
RETAILER LAYOUT DESIGN: A NOVEL HYBRID APPROACH WITH ASSOCIATION RULES MINING AND MCRAFT
by Ali Osman Ku?akc?, Elif Karakaya
Abstract: Spatial layout of a retail store is a crucial decision variable related to both utilisation of store area and purchasing behaviour of the customer. In this respect, the task of optimising the allocation of shelves to specific product segments has become a strategic decision to facilitate a more comfortable shopping environment for customers, which, in turn, increases sales volume. This study proposes a novel hybrid approach to facility layout design problem, which combines association rules mining (ARM) and a facility layout method, MCRAFT. The proposed methodology is composed of two main stages: 1) rule mining; 2) layout design. More specifically, the presented approach exploits the association rules obtained from purchasing records and uses them as a proximity measure input to MCRAFT algorithm to determine the layout of the store. The merit of the proposed methodology is shown with a case study on a prominent Turkish supermarket chain.
Keywords: Association Rule Mining; Facility Layout Algorithm; Supermarket Layout; Apriori Algorithm.
Minimizing Makespan in Embedded Real-Time Systems with Failure Rate Requirements
by Hamoudi Kalla, Salim Kalla, Sonia Sabrina Bendib, Riadh Hocine
Abstract: Scheduling of real-time tasks in embedded real-time systems with quantitative reliability requirements, such as failure rate, is one of the important issues in system design. In this paper, we present a real-time scheduling heuristic that minimise makespan and satisfy reliability requirements for systems that are subject to processor and communication faults. The heuristic is based on a cost function to minimise makespan and on task redundancy to meet reliability requirements. Our approach is dedicated to heterogeneous architectures with multiple processors linked by several shared buses. It is based on active redundancy and data fragmentation strategies, which allow fast error detection and error handling. Thanks to the above-mentioned strategies, we are able to show with simulation results that our approach can generally reduce the run-time overhead.
Keywords: task scheduling; embedded systems; real-time systems; makespan; failure rate; reliability; task redundancy.
PSO-based algorithm for solving lot splitting in unbalanced seru production systems
by Zhe Zhang, Yong Yin, Luming Shao
Abstract: Seru production system is one of responsive and flexible systems to cope with uncertain demands or changes in current volatile market, and the design of this system involves many structural and operational factors. One of the most important steps is the formation of seru production system, including worker assignment and order scheduling. This paper aims to address a scheduling problem in unbalanced seru production system with lot splitting, where the non-zero setup time is also considered. After describing the problem, a comprehensive mathematical model is proposed to confirm seru formations and arrange orders to different serus. Subsequently, motivated by the particular nature of proposed model, a solution method based on PSO algorithm is designed to assign workers to each seru and determine the productivity, and the optimal assignment of sub-orders is also decided. Finally, an illustrative numerical example is presented to validate the effectiveness of proposed model and solution method.
Keywords: Line-seru conversion; scheduling; lot splitting; particle swarm optimization.
Coupling Influence of Multiple Disruptions in Supply Chain
by Hui Hu, Hai Ma, Jing He, Baowen Li, Yang Gao
Abstract: To analyse the coupling influence of multiple disruptions, this study proposed a coupling utility model of multiple disruptions in a supply chain. The model was constructed based on the two functions of utility and degree of coupling. Then the supply chain model under disruptions was built and Anylogic was applied to simulate the coupling influence on the supply chain system. Taking the fire-explosion at the Port of Tianjin as an example, the coupling utility degree between disruptions was calculate. Then the simulation results were obtained to analyse the coupling influence under various characteristics of disruptions. Results show that the proposed methodology could analyse the coupling influence quantitatively and visually. The intensity coefficient of disruption is more significant than its frequency coefficient for the case. The research will provide reference for the control of multiple disruptions.
Keywords: supply chain; multiple disruptions; coupling; utility; simulation.
Analysis of the performance of competing models for aggregate demand forecasting using observable data characteristics
by Rajagopalan Sridharan, N. Jayasree, Radha Ramanan
Abstract: This paper provides an analysis of the performance of two simplified approaches for forecasting the aggregate demand for a product family consisting of two interrelated items. The correlated demand characteristic of the product family is modelled by bivariate vector IMA(1, 1) process. The forecasting approaches chosen for evaluation are univariate scheme and aggregate scheme. The performances of these methods are analysed by theoretically determining the forecast mean square error (MSE) in terms of observable data characteristics. Further, subsequent evaluation of percentage changes of these MSEs with respect to the MSE of original bivariate model has been conducted to determine how far the forecast MSE values deviate from the original model. Through numerical experimentation, the necessary and sufficient conditions in terms of observable data characteristics are determined for the two approaches to be equal in terms of forecast MSE of the original bivariate model.
Keywords: Aggregate demand forecast; Vector IMA (1,1) model; observable data characteristics.
Modeling and optimization of duplex turning of titanium alloy (grade 5) using Taguchi methodology-response surface methodology (TM-RSM)
by Sunil Kumar, Ravindra Nath Yadav, Raghuvir Kumar
Abstract: Duplex turning is an innovative idea of metal cutting that shows potential to improve the productivity with better quality. In duplex turning, two cutting tools are used as parallel to each other and perpendicular to the workpiece axes for getting the desired surface quality in single pass turning operation. The use of two cutting tools makes the process very complex which requires optimal parameters to enhance the productivity with quality. In present work, the parameters are optimised by applying a Taguchi methodology (TM) and optimised parameters are utilised as central values for further analysis. The central data are used to collect the experimental results for response surface methodology (RSM) for modelling and optimisation of control parameters such as cutting speed, feed rate, primary depth-of-cut (DOC) and secondary-DOC to optimise responses as primary-cutting force, secondary-cutting force and average surface roughness using TM-RSM techniques. The result shows the significant improvement in the responses with TM-RSM approach as primary-cutting force = 18.67%, secondary-cutting force = 15.80% and surface finish = 13.30% than the TM optimised values.
Keywords: Cutting Force; RSM; Surface Roughness; Taguchi; Turning; Modeling: Optimization; ANOVA.
Inventory- Routing Mathematical Model in Transportation Fleet of a Bike Sharing Distribution Network
by Hadi Shirouyehzad, Mahsa Soroushnia
Abstract: Todays, bike sharing system as a non-motorised transportation system and compatible with the environment has attracted a lot of attention in the field of public transportation. One of the issues that has been considered by some researchers in recent years is bike sharing rebalancing problem that is related to the provision of the required bike for stations and their inventory management. The proposed model is an integer nonlinear programming that is able to rebalance BSS by considering the appropriate inventory policies. The purpose of this model is finding optimal routes for the fleet of vehicles (trucks) and using the suitable trucks to traverse these routes and minimising costs of rebalancing operations in multiple periods. The efficiency of the model is proved by solving two numerical examples by the GAMS software.
Keywords: Bike Sharing System (BSS); Bike sharing Rebalancing Problem (BRP); Inventory-Routing Problem (IRP); Mathematical Modelling.
Effects of Supply Disruption on Optimal Inventory Policy: The Case of (r,S) Continuous Review Inventory Policy
by Chirakiat Saithong, Huynh Trung Luong
Abstract: In this study, we focus on the derivation of an optimal inventory policy to help tackle the supply disruption problem. The main objective of the study is to derive an optimal inventory policy for a retailer who is facing stochastic supply disruption and stochastic demand, operating under a (r, S) continuous review policy so as to minimise the total inventory cost per time-unit. Renewal reward theorem is used to help develop the total inventory cost function which consists of order cost, time-dependent holding and shortage costs in the existence of replenishment lead time. Numerical experiments and sensitivity analyses are then conducted to illustrate the applicability of the developed inventory policy.
Keywords: Supply disruption; continuous review inventory policy; stochastic demand; renewal reward process; expected path approach.
Ranking of Univariate Forecasting Techniques for Seasonal Time Series using Analytical Hierarchy Process
by Sharfuddin Ahmed Khan, Iram Naim, Tripti Mahara
Abstract: The choice of a suitable forecasting method carries noteworthy significance for organisations in adequately accomplishing their business targets. The selection of forecasting method becomes more sophisticated when there is a significant impact of seasonality on the business of an organisation. To deal with the situation of selecting the most relevant forecasting method for seasonal data, this paper proposes a framework using analytical hierarchy process (AHP) to rank various forecasting techniques for long time series. Accuracy measures namely Theils U, mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) are used as AHP criteria for performance measurement of various univariate time series methods such as na
Keywords: Time Series Analysis; Forecasting; AHP; Seasonality; TBATS; SARIMA; Accuracy Measures.
Impact of consumption behaviour on stock-induced material waste
by Neeta Sharma, Prem Vrat
Abstract: This paper attempts to examine the impact of consumption behaviour on material waste due to stock-induced consumption phenomenon and introduces an entirely new behavioural dimension to inventory management practices. Stock-induced consumption phenomenon is linked with material waste and a case of water resource wastage due to stock-induced consumption is analysed here from the behavioural perspective. To analyse the behavioural aspects in water resource wastage, a MATLAB simulation program is developed by taking reference of one of the available stock-induced consumption inventory control models. The results obtained in the form of indifference curves reveal the conspicuous increase in water waste due to poor behavioural traits. Based on the results obtained, a concept of behavioural consumption grid is developed to provide insights which can be used in devising policies for reducing stock-induced material waste.
Keywords: stock-induced consumption; behavioral grid; indifference curve; simulation; behavioural parameter; behavioural inventory management; material waste.
Application of Artificial Immune System Algorithm for Simultaneous Minimization of Multiple Objectives in Single Row Facility Layout Problems
by Lenin N, Siva Kumar Mahalingam, Jayakrishna K, Selvakumar G
Abstract: In this paper, an artificial immune system (AIS) algorithm is proposed to solve single row facility layout problem (SRFLP) for obtaining a best layout design of machines, which simultaneously minimises the multiple objectives. The multi-product environment with multiple objectives is considered in this work and it is a non-polynomial hard problem too. Total number of machines in the layout, total flow distance of products, total length of the flow line and total material handling cost are considered as objectives. Four problems are taken from Lenin et al. (2018) and four problems are randomly generated to obtain the best layout using AIS. The reduction in objective values is good by the proposed AIS algorithm compared with Lenin et al. (2018). In addition, the computational time for all the eight problems by the proposed AIS method is less compared with Lenin et al. (2018).
Keywords: Artificial Immune System Algorithm; Single Row Facility Layout Problem; Best Layout; Multi-Product Environment; Multiple Objectives.
Usability in computerized mobile assistance solutions
by Dorra Zaibi, Meriem Riahi, Faouzi Moussa
Abstract: The awareness of the importance of system usability is in a constant boosting. Considering usability has been more and more recognised as one of the indispensable quality factors in the success of an interactive system. This paper explores in this direction the importance of usability in context-aware user interface design for computerised mobile maintenance solutions. We propose a methodology for incorporating contextualised usability requirements in the development process of mobile applications in industrial maintenance sector. An illustrative case study was presented in a typical industrial environment to validate our proposal. Finally, an experimental evaluation was conducted with end users to evaluate our proposal.
Keywords: Mobile industrial maintenance; computerized management maintenance system; usability; context-awareness; human-computer interface; model-driven development.
An Effective Approach for Aid Planning on Multi-Type Transportation Networks After a Disaster
by Saber Shiripour, Nezam Mahdavi-Amiri
Abstract: We present a new approach for emergency response planning to the injured on a multi-type transportation network. We consider a three-type transportation network with separate connection links simultaneously: road, rail and air networks. In this study, a circle-based approach is presented where using concentric circles with various radiuses, different levels of the effect of a disaster are considered. After formulating the relations, we present an integer nonlinear programming model for the problem. The model is to determine the locations for establishment of temporary aid stations among the candidate locations, the type of aid stations, the percentage of the injured allocated to each station, the percentages of the injured allocated to different routes and the number of vehicles and the type of transportation network so that the total relief time is minimised. Finally, we test and analyse a numerical example of the earthquake problem in a typical transportation network in detail.
Keywords: Location-allocation-routing problem; Multi-type transportation network; Disaster response; Mathematical programming model.
An efficient teaching-learning-based optimization algorithm (TLBO) for the resource-constrained project scheduling problem
by Dheeraj Joshi, M.L. Mittal, Manish Kumar
Abstract: This work proposes a teaching-learning-based optimisation algorithm as an alternate metaheuristic to solve the resource-constrained project scheduling problem (RCPSP). A precedence feasible activity list is employed for encoding the solutions whereas serial schedule generation scheme (SGS) is used as the decoding procedure to derive the solutions. In order to have good initial population, we employ a regret-based sampling method with latest finish time (LFT) priority rule. In addition to teacher and learner phase in basic TLBO, the proposed work also applies two additional phases namely self-study and examination for improving its exploration and exploitation capabilities. The algorithm is tested on well-known instance sets from literature. The performance of the algorithm is found to be competitive with the existing solution approaches available to solve this problem.
Keywords: Resource-constrained project scheduling; metaheuristics; teaching-learning-based optimization algorithm.
Modular product architecture to manage product development complexity
by Ahm Shamsuzzoha, Sujan Piya, Petri Helo, Mohammed Alkahtani
Abstract: Shorter product life cycles, together with heterogeneous market demands, are forcing manufacturing companies to eliminate or reduce complexities in product development and supply chain. These complexities arise due to high level of interdependencies between component interfaces and supply chain participants. To address such complexities, companies need to focus on their product architecture and supply chain design. In this research, the impact of product architecture on developing modular products is highlighted. This modular principle is elaborated with the objective to reduce product development complexities. A case example is presented to define the importance of product architecture with the help of a design structure matrix (DSM) tool to reduce product development complexity. In addition, various drivers responsible for supply chain complexities are identified and categorised, and the relationship between product architecture and supply chain complexities are defined within the scope of this research.
Keywords: Product architecture; design structure matrix; product modularity; product complexity; case study.
Factors Affecting Spine Loading in a Box Lifting Task: A Digital Human Modeling Study
by Osama Al-meanzel, Faisal Aqlan, Abd Al-Rahman S. Al-Shudiefat, Hesham A. Almomani
Abstract: This paper presents a digital human modelling (DHM) study of a box-lifting task considering human physical characteristics (i.e., gender and percentile) and task requirements (i.e., posture and force). Two response variables are considered: compression force on L4/L5 and the tension on right/left Latissimus Dorsi muscle. Multivariate analysis of variance (MANOVA) was used to analyse the data. Results showed that lower back compression force is positively correlated with Latissimus Dorsi muscle tension (r = 0.94). Moreover, the 95th percentile male in standing position experienced the highest compression force on the lower back; however, both males and females had similar muscle tension.
Keywords: Lower back disorders; lifting; manual material handling; digital human modeling,.
Analyzing challenges for Internet of Things adoption in agriculture supply chain management
by Sunil Luthra, SANJEEV YADAV, Dixit Garg
Abstract: Internet of things (IoT) has gained noticed throughout the world. It has changed the agricultural supply chain and permits farmers and food processing organisation to compete with massive issues they face. Currently, IoT is at developing stage for its implementation in agriculture supply chain (ASC). Therefore, purpose of this paper is the identification of critical challenges in IoT adoption for ASC. In this paper technique of order preference similar to ideal solution (TOPSIS) methodology adopted to prioritise the identified challenges. Findings introduce some recent technology in IoT field and also ten critical challenges in IoT adoption. This paper concluded that IoT-based infrastructure for ASC is the most important challenge and IoT-based cloud system is the worst challenge. This paper also has managerial implications for organisations managers to adopt IoT in the ASC to improve their competitiveness. This paper may be further used in various Industry 4.0 applications.
Keywords: Internet of Things (IoT); Agriculture Supply Chain (ASC); Technique of Order Preferences Similar to Ideal Solution (TOPSIS); Radio Frequency Identification (RFID).