A Metaheuristic Based Self-Reasoning System for Assembly Sequence Automation in CIM

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Beykent Üniversitesi

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Assembly sequencing task is a time consuming process. In traditional manufacturing, it requires human planning in order to decide which sequence will be traced to assembly the parts. Even in some modern Computer Integrated Manufacturing (CIM) environments coupled with assembly robots after human operated sequence determination, the route of assembly robot are coded to robot control unit. Automation of this process, of course, will eliminate the error caused by human factor and drop the cost of product. Thus, the objective of paper is to determine intelligently configuration of robot movements for a number of parts that will be assembled. A prototype of gantry-type robot operating as a material handing device for an assembly automation system was designed and produced. Three metaheuristic techniques, Genetic Algorithm (GA), Simulated Annealing (SA) and Tabu Search (TS), were employed to decide the shortest path of assembly sequence. Then, the optimum assembly configuration found by one or more techniques was passed automatically to a control unit to carry out assembly tasks. The algorithms are shown to be effective regarding the results obtained. The model developed can be employed as a self-reasoning system for facilitating automation of assembly in a CIM environment.


Anahtar Kelimeler

Genetic Algorithm (GA), Simulated Annealing (SA), Tabu Search (TS), Gantry-type robot, Assembly automation


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Journal of Science and Technology 2 (1), 2008, 99-114