Optimum machine capabilities for reconfigurable manufacturing systems

Reconfigurable manufacturing systems constitute a new manufacturing paradigm and are considered as the future of manufacturing because of their changeable and flexible nature. In a reconfigurable manufacturing environment, basic modules can be rearranged, interchanged, or modified, to adjust the pro...

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Vydané v:	International journal of advanced manufacturing technology Ročník 95; číslo 9-12; s. 4397 - 4417
Hlavní autori:	Asghar, Eram, Zaman, Uzair Khaleeq uz, Baqai, Aamer Ahmed, Homri, Lazhar
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Springer London 01.04.2018 Springer Nature B.V Springer Verlag
Predmet:	CAE) and Design Computer-Aided Engineering (CAD Configurations Engineering Genetic algorithms Industrial and Production Engineering Machine tools Machining Manufacturing Manufacturing cells Mathematics Mechanical Engineering Media Management Modular structures Modules Multiple objective analysis Optimization Original Article Process planning Production capacity Reconfiguration Reconfigurable manufacturing systems Multi-objective genetic algorithm Alternative process plans Reconfigurable process plans
ISSN:	0268-3768, 1433-3015
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Abstract	Reconfigurable manufacturing systems constitute a new manufacturing paradigm and are considered as the future of manufacturing because of their changeable and flexible nature. In a reconfigurable manufacturing environment, basic modules can be rearranged, interchanged, or modified, to adjust the production capacity according to production requirements. Reconfigurable machine tools have modular structure comprising of basic and auxiliary modules that aid in modifying the functionality of a manufacturing system. As the product’s design and its manufacturing capabilities are closely related, the manufacturing system is desired to be customizable to cater for all the design changes. Moreover, the performance of a manufacturing system lies in a set of planning and scheduling data incorporated with the machining capabilities keeping in view the market demands. This research work is based on the co-evolution of process planning and machine configurations in which optimal machine capabilities are generated through the application of multi-objective genetic algorithms. Furthermore, based on these capabilities, the system is tested for reconfiguration in case of production changeovers. Since, in a reconfigurable environment, the same machine can be used to perform different tasks depending on the required configuration, the subject research work assigns optimum number of machines by minimizing the machining capabilities to carry out different operations in order to streamline production responses. An algorithm has also been developed and verified on a part family. As a result of the proposed methodology, an optimized reconfigurable framework can be achieved to realize optimal production of a part family. Finally, the proposed methodology was applied on a case study and respective conclusions were drawn.
AbstractList	Reconfigurable manufacturing systems constitute a new manufacturing paradigm and are considered as the future of manufacturing because of their changeable and flexible nature. In a reconfigurable manufacturing environment, basic modules can be rearranged, interchanged, or modified, to adjust the production capacity according to production requirements. Reconfigurable machine tools have modular structure comprising of basic and auxiliary modules that aid in modifying the functionality of a manufacturing system. As the product’s design and its manufacturing capabilities are closely related, the manufacturing system is desired to be customizable to cater for all the design changes. Moreover, the performance of a manufacturing system lies in a set of planning and scheduling data incorporated with the machining capabilities keeping in view the market demands. This research work is based on the co-evolution of process planning and machine configurations in which optimal machine capabilities are generated through the application of multi-objective genetic algorithms. Furthermore, based on these capabilities, the system is tested for reconfiguration in case of production changeovers. Since, in a reconfigurable environment, the same machine can be used to perform different tasks depending on the required configuration, the subject research work assigns optimum number of machines by minimizing the machining capabilities to carry out different operations in order to streamline production responses. An algorithm has also been developed and verified on a part family. As a result of the proposed methodology, an optimized reconfigurable framework can be achieved to realize optimal production of a part family. Finally, the proposed methodology was applied on a case study and respective conclusions were drawn.
Author	Zaman, Uzair Khaleeq uz Asghar, Eram Homri, Lazhar Baqai, Aamer Ahmed
Author_xml	– sequence: 1 givenname: Eram surname: Asghar fullname: Asghar, Eram organization: Ghulam Ishaq Khan Institute of Engineering Sciences and Technology – sequence: 2 givenname: Uzair Khaleeq uz surname: Zaman fullname: Zaman, Uzair Khaleeq uz email: uzair-khaleeq-uz.zaman@ensam.eu organization: Laboratoire de Conception Fabrication Commande, École nationale supérieure d’arts et métiers – sequence: 3 givenname: Aamer Ahmed surname: Baqai fullname: Baqai, Aamer Ahmed organization: National University of Sciences and Technology – sequence: 4 givenname: Lazhar surname: Homri fullname: Homri, Lazhar organization: Laboratoire de Conception Fabrication Commande, École nationale supérieure d’arts et métiers
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Keywords	Reconfigurable manufacturing systems Multi-objective genetic algorithm Alternative process plans Reconfigurable process plans
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Snippet	Reconfigurable manufacturing systems constitute a new manufacturing paradigm and are considered as the future of manufacturing because of their changeable and...
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SubjectTerms	CAE) and Design Computer-Aided Engineering (CAD Configurations Engineering Genetic algorithms Industrial and Production Engineering Machine tools Machining Manufacturing Manufacturing cells Mathematics Mechanical Engineering Media Management Modular structures Modules Multiple objective analysis Optimization Original Article Process planning Production capacity Reconfiguration
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Title	Optimum machine capabilities for reconfigurable manufacturing systems
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