Modularity-based quality assessment of a disruptive reconfigurable manufacturing system-A hybrid meta-heuristic approach
This study considers quality aspects in the process planning of a reconfigurable manufacturing system. The goal is to analyze how the variation in quality impacts the process planning, i.e., cost-based design and modular features. Besides this, the analysis helps in identifying the number of conform...
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| Published in | International journal of advanced manufacturing technology Vol. 115; no. 5-6; pp. 1421 - 1444 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Springer London
01.07.2021
Springer Nature B.V Springer Verlag |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0268-3768 1433-3015 1433-3015 |
| DOI | 10.1007/s00170-021-07229-6 |
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| Abstract | This study considers quality aspects in the process planning of a reconfigurable manufacturing system. The goal is to analyze how the variation in quality impacts the process planning, i.e., cost-based design and modular features. Besides this, the analysis helps in identifying the number of conforming and failed products delivered by a process plan. First, a multi-objective mixed integer non-linear programming model is proposed that contains the novel objectives of cost, quality decay, and modular efforts. Secondly, the model is implemented on an industrial case study by using an exact solution approach and a novel hybrid version of two popular meta-heuristics, namely non-sorting genetic algorithm and multi-objective particle swarm optimization. The hybrid heuristic helps strengthening the application of approaches by creating a balance in searching the solution space. The performance of different approaches is assessed by using two metrics and two termination criteria. The findings will help the decision-makers in assessing how quality-related issues impact the choice of a process plan and in understanding the trade-off among cost, quality, and modularity. Finally, conclusion and future research avenues are provided. |
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| AbstractList | This study considers quality aspects in the process planning of a reconfigurable manufacturing system. The goal is to analyze how the variation in quality impacts the process planning, i.e., cost-based design and modular features. Besides this, the analysis helps in identifying the number of conforming and failed products delivered by a process plan. First, a multi-objective mixed integer non-linear programming model is proposed that contains the novel objectives of cost, quality decay, and modular efforts. Secondly, the model is implemented on an industrial case study by using an exact solution approach and a novel hybrid version of two popular meta-heuristics, namely non-sorting genetic algorithm and multi-objective particle swarm optimization. The hybrid heuristic helps strengthening the application of approaches by creating a balance in searching the solution space. The performance of different approaches is assessed by using two metrics and two termination criteria. The findings will help the decision-makers in assessing how quality-related issues impact the choice of a process plan and in understanding the trade-off among cost, quality, and modularity. Finally, conclusion and future research avenues are provided. This study considers quality aspects in the process planning of a reconfigurable manufacturing system. The goal is to analyzehow the variation in quality impacts the process planning, i.e., cost-based design and modular features. Besides this, the analysishelps in identifying the number of conforming and failed products delivered by a process plan. First, a multi-objective mixedinteger non-linear programming model is proposed that contains the novel objectives of cost, quality decay, and modular efforts.Secondly, the model is implemented on an industrial case study by using an exact solution approach and a novel hybrid version oftwo popular meta-heuristics, namely non-sorting genetic algorithm and multi-objective particle swarm optimization. The hybridheuristic helps strengthening the application of approaches by creating a balance in searching the solution space. The performanceof different approaches is assessed by using two metrics and two termination criteria. The findings will help the decisionmakersin assessing how quality-related issues impact the choice of a process plan and in understanding the trade-off among cost,quality, and modularity. Finally, conclusion and future research avenues are provided. |
| Author | Dantan, Jean Yves Khan, Abdul Salam Homri, Lazhar Siadat, Ali |
| Author_xml | – sequence: 1 givenname: Abdul Salam surname: Khan fullname: Khan, Abdul Salam email: abdul_salam.khan@ensam.eu, abdul.islam@nbs.nust.edu.pk organization: Arts et Métiers Institute of Technology, Université de Lorraine, LCFC, HESAM Université, Department of Operations and Supply Chain, NUST Business School, National University of Sciences and Technology (NUST) – sequence: 2 givenname: Lazhar surname: Homri fullname: Homri, Lazhar organization: Arts et Métiers Institute of Technology, Université de Lorraine, LCFC, HESAM Université – sequence: 3 givenname: Jean Yves surname: Dantan fullname: Dantan, Jean Yves organization: Arts et Métiers Institute of Technology, Université de Lorraine, LCFC, HESAM Université – sequence: 4 givenname: Ali surname: Siadat fullname: Siadat, Ali organization: Arts et Métiers Institute of Technology, Université de Lorraine, LCFC, HESAM Université |
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| Keywords | Reconfigurable manufacturing system Reconfigurable process plan Multi-objective optimization Quality assessment Variation Cost Hybrid heuristics |
| Language | English |
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| Title | Modularity-based quality assessment of a disruptive reconfigurable manufacturing system-A hybrid meta-heuristic approach |
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