Comparing sequential and integrated models in Reconfigurable Manufacturing Systems optimization

Consumers are increasingly seeking products with a higher degree of customization, and this has intensified the search for more flexible production systems. Unexpected phenomena, including those impacting the economy and public health, have shown the need for high reactivity by manufacturers. Reconf...

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Published in:IJIEM. International Journal of Industrial Engineering and Management (Online) Vol. 15; no. 2; pp. 140 - 155
Main Authors: I Barros Garcia, Daaboula, J, Jougletb, A, Le Duigoua, J
Format: Journal Article
Language:English
Published: Novi Sad University of Novi Sad 01-06-2024
University of Novi Sad, Technical faculty Mihajlo Pupin, Zrenjanin
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Abstract Consumers are increasingly seeking products with a higher degree of customization, and this has intensified the search for more flexible production systems. Unexpected phenomena, including those impacting the economy and public health, have shown the need for high reactivity by manufacturers. Reconfigurable Manufacturing Systems are one of the means to respond to new market needs. They are designed to be able to quickly change their structure and thus adapt their functionalities and capabilities. A central question with regard to these types of systems is when and how they should be reconfigured. It is, however, a question that needs to be addressed simultaneously alongside the classic resource allocation and scheduling problems, since the problems are interdependent. This paper proposes four models that address the problem sequentially, partially sequentially, and integrally. Our numerical analysis demonstrates the advantage and importance of treating these problems in an integrated manner. In addition, we provide and compare three exact methods for the integrated process planning, layout, and scheduling optimization problems. The exact methods are integer linear programming, constraint programming, and constraint programming with search strategies, which our numerical examples show to be greatly superior to the two others. Finally, we present a problem at an industrial scale.
AbstractList Consumers are increasingly seeking products with a higher degree of customization, and this has intensified the search for more flexible production systems. Unexpected phenomena, including those impacting the economy and public health, have shown the need for high reactivity by manufacturers. Reconfigurable Manufacturing Systems are one of the means to respond to new market needs. They are designed to be able to quickly change their structure and thus adapt their functionalities and capabilities. A central question with regard to these types of systems is when and how they should be reconfigured. It is, however, a question that needs to be addressed simultaneously alongside the classic resource allocation and scheduling problems, since the problems are interdependent. This paper proposes four models that address the problem sequentially, partially sequentially, and integrally. Our numerical analysis demonstrates the advantage and importance of treating these problems in an integrated manner. In addition, we provide and compare three exact methods for the integrated process planning, layout, and scheduling optimization problems. The exact methods are integer linear programming, constraint programming, and constraint programming with search strategies, which our numerical examples show to be greatly superior to the two others. Finally, we present a problem at an industrial scale.
Author Daaboula, J
Jougletb, A
I Barros Garcia
Le Duigoua, J
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Snippet Consumers are increasingly seeking products with a higher degree of customization, and this has intensified the search for more flexible production systems....
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SubjectTerms Constraints
Integer programming
Linear programming
Manufacturing
Numerical analysis
Optimization
Process planning
Public health
Questions
Reconfiguration
Resource allocation
Resource scheduling
Search methods
Title Comparing sequential and integrated models in Reconfigurable Manufacturing Systems optimization
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