Self-Evolution of an Assembly Workshop in Knowledgeable Manufacturing Environment

Abstract:

In this study, the self-evolution problem of knowledgeable manufacturing systems is studied by taking an assembly workshop as an example. The rolling horizon procedure (RHP) is adopted to implement the self-evolution process of the workshop. The whole dynamic self-evolution process is decomposed into several static decision processes. At each decision point, a static decision sub-problem needs to be solved. A general mathematical model of these sub-problems is built, and a bi-level genetic algorithm (BiGA) is designed. Simulation results show that the model and algorithm are feasible and effective. By comparison, the system with self-evolution operations has a better production performance.

• Periodical: Applied Mechanics and Materials (Volumes 602-605)
• Pages: 623-628
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.602-605.623
• Online since: August 2014
• Authors: Tian Hua Jiang*, Hong Sen Yan
• Keywords: Assembly Workshop, BiGA, Knowledgeable Manufacturing, RHP, Self-Evolution

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