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 inInternational journal of advanced manufacturing technology Vol. 115; no. 5-6; pp. 1421 - 1444
Main Authors Khan, Abdul Salam, Homri, Lazhar, Dantan, Jean Yves, Siadat, Ali
Format Journal Article
LanguageEnglish
Published London Springer London 01.07.2021
Springer Nature B.V
Springer Verlag
Subjects
Online AccessGet full text
ISSN0268-3768
1433-3015
1433-3015
DOI10.1007/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.
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
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Issue 5-6
Keywords Reconfigurable manufacturing system
Reconfigurable process plan
Multi-objective optimization
Quality assessment
Variation
Cost
Hybrid heuristics
Language English
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Snippet This study considers quality aspects in the process planning of a reconfigurable manufacturing system. The goal is to analyze how the variation in quality...
This study considers quality aspects in the process planning of a reconfigurable manufacturing system. The goal is to analyzehow the variation in quality...
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SubjectTerms CAE) and Design
Computer-Aided Engineering (CAD
Cost analysis
Decision making
Engineering
Engineering Sciences
Exact solutions
Genetic algorithms
Heuristic methods
Hybrid systems
Industrial and Production Engineering
Linear programming
Mechanical Engineering
Mechanics
Media Management
Mixed integer
Modular design
Modularity
Multiple objective analysis
Nonlinear programming
Original Article
Particle swarm optimization
Process planning
Quality assessment
Reconfiguration
Solution space
Sorting algorithms
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Title Modularity-based quality assessment of a disruptive reconfigurable manufacturing system-A hybrid meta-heuristic approach
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