A holistic approach to manufacturing cell formation: Incorporation of machine flexibility and machine aggregation
| Autor: | Felix T.S. Chan, P.L.Y. Chan, KW Lau |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Flexibility (engineering)
Engineering Operations research Process (engineering) business.industry Mechanical Engineering Cellular manufacturing Simple cell Industrial engineering Industrial and Manufacturing Engineering medicine.anatomical_structure Group technology Genetic algorithm medicine Factory (object-oriented programming) Routing (electronic design automation) business |
| Zdroj: | Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 218:1279-1296 |
| ISSN: | 2041-2975 0954-4054 |
| Popis: | One of the most practical approaches of improving productivity in a factory is to adopt the superior concept and technique of cellular manufacturing (CM) based on group technology (GT). Particularly, cell formation is an important, critical and difficult step in CM. In general, there have been a number of methodologies proposed for solving a machine-part grouping problem (MPGP). Besides considering the simple cell formation problem, some researchers have focused on machine flexibility, in which parts are having alternative routeings/process plans. However, it is very rare to consider the area of aggregation and disaggregation of machines in cell formation under uncertain constraints and uncertainty. In the light of this, the main aim of this present work is to address the MPGP holistically with the considerations of machine flexibility as well as machine aggregation and disaggregation simultaneously. In addition, based on the availability of alternative routeings, a method is proposed to generate an alternative solution for machine breakdown situations. Thus, the problem nature of this work will be more realistic and practical for today's global manufacturing era. The problem scope has been identified and the model is formulated in mathematical programming form. The objective function of this model is to minimize the total intercellular and intracellular part movement. Since MPGP has been proved to be non-polynomial (NP) complete, a genetic algorithm (GA), which is an excellent optimization technique, is employed to solve this problem. |
| Databáze: | OpenAIRE |
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