PERFORMANCE BASED OPTIMALMACHINE ASSIGNMENT IN RECONFIGURABLE MANUFACTURING SYSTEM USING GENETIC ALGORITHM

The Reconfigurable Machine Tools (RMTs) or Reconfigurable Machines (RMs) are considered to be the core components of anyReconfigurable Manufacturing System (RMS). The presence of these RMTs or RMs on the shop floor directly governs the reconfigurability of the manufacturing system. Reconfigurable machines have integrable-modular structure consist of basic and auxiliary modules along with the open architecture software to facilitate the reconfiguration process. Several potential RMTs can be assembled using these modules which may vary in their functionalities and capacities. For any candidate operation, multiple machine configurations may be selected. The selection of any desired machine configuration not only determines the performance of the present system configuration but it also governs the reconfiguration of the RMT for other upcoming operations intended to be performed in future. Thus, selecting the optimal machine configuration across stagesof any serial production line has direct impacton theperformance and subsequent reconfiguration of the system. In the present paper, a genetic algorithm based methodology has been proposed for optimalselection of machine alternatives across stages of the production line. The optimal selection is based on multiple performances parameters which includes minimizing the production cycle time and maximizing the operational capability of the production line. The developed approach is demonstrated with the help of a numerical illustration. For the considered numerical problem, the optimal results obtained are 3 4 mc , 2 5 mc and 2 1 mc for stages-1,2 and 3 respectively as selected machine configuration with a fitness value of 6.8326. The other feasible configurations so obtained are presented and are ranked on the basis of fitness values.