Manufacturing process planning optimisation in reconfigurable multiple parts flow lines

• Autorzy: Ismail N. , Musharavati F. , Hamouda A. S. M. , Ramli A. R.
• Języki publikacji: EN

Abstrakty

EN

Purpose: This paper explores the capabilities of genetic algorithms in handling optimization of the critical issues mentioned above for the purpose of manufacturing process planning in reconfigurable manufacturing activities. Two modified genetic algorithms are devised and employed to provide the best approximate process planning solution. Modifications included adapting genetic operators to the problem specific knowledge and implementing application specific heuristics to enhance the search efficiency. Design/methodology/approach: The genetic algorithm methodology implements a genetic algorithm that is augmented by application specific heuristics in order to guide the search for an optimal solution. The case study is based on the manufacturing system. Raw materials enter the system through an input stage and exit the system through an output stage. The system is composed of sixteen (16) processing modules that are arranged in four processing stages. Findings: The results indicate that the two genetic algorithms are able to converge to optimal solutions in reasonable time. A computational study shows that improved solutions can be obtained by implementing a genetic algorithm with an extended diversity control mechanism. Research limitations/implications: This paper has examined the issues of MPP optimization in a reconfigurable manufacturing framework with the help of a reconfigurable multiparts manufacturing flow line. Originality/value: The results of the case illustration have demonstrated the practical use of diversity control implemented in the MGATO technique. In comparison to MGAWTO, the implemented MGATO improves the population diversity through a customized threshold operator. It was clear that the MGATO can obtain better solution quality by foiling the tendency towards premature convergence.

Słowa kluczowe

EN

reconfigurable manufacturing; manufacturing process planning optimisation; process selection; process sequencing; parts loading scheduling

PL

rekonfiguracja systemu produkcji; proces selekcji; proces sekwencjonowania

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2008
• Tom: Vol. 31, nr 2
• Strony: 671--677
• Opis fizyczny: Bibliogr. 7 poz., wykr., tab.

Twórcy

autor

Ismail N.

autor

Musharavati F.

autor

Hamouda A. S. M.

autor

Ramli A. R.

• Department of Mechanical and Manufacturing Engineering Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia,

Bibliografia

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• [2] Y. Koren, U. Heisek, F. Jovane, T. Moriwaki, G. Prischow, G. Ulsoy, H. Van Brussel, Reconfigurable manufacturing systems, Annals of the CIRP 48/2 (1999) 527-540.
• [3] G. H. Ma, Y. F. Zhang, A. Y. C. Nee, A simulated annealingbased optimization algorithm for process planning, International Journal of Production Research 38/12 (2000) 2671-2687.
• [4] M. Marefat, J. Britanik, Automated reuse of some solutions in manufacturing process planning through a case-based approach, Proceedings of the ASME Design Engineering Technical Conference, DETCI 1996/CIE-1344, 1996.
• [5] Li Tang, D. M. Yip-Hoi, W. Wang, Y. Koren, Concurrent line-balancing, equipment selection and throughput analysis for multi-part optimal line design, Proceedings of the 2nd CIRP Conference on Reconfigurable Manufacturing Systems, Ann Arbor USA, 2003.
• [6] Y. F. Zhang, A. Y. C. Nee, Applications of genetic algorithms and simulated annealing in process planning optimization, in Computational Intelligence in Manufacturing Handbook, Wang and Kusiak (Eds), 2001.
• [7] F. Zhang, Y. F. Zhang, A. Y .C. Nee, Using genetic algorithms in process planning for job shop machining, IEE Transactions on Evolutionary Computation 1/4 (1997) 278-289.