Evolutionary Algorithm Technique to Optimize Configurational Cost in Reconfigurable Manufacturing System
Suresh Babu G1, N. Chikkanna2
1Suresh Babu G., Research Scholar, VTU Research Resource Centre, Belagavi, Karnataka, India.
2Dr. N. Chikkanna, Professor, Department of Aerospace propulsion technology, VTU VIAT, Muddenahalli, Chickballapur, Karnataka, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1283-1290 | Volume-8 Issue-6, March 2020. | Retrieval Number: E6037018520/2020©BEIESP | DOI: 10.35940/ijrte.E6037.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In past few decades, manufacturing industry has been trying to achieve the high quality customized products in the flexible batches. Moreover due to the dynamic demand of market, the product lifecycle and flexibility is one of the major concern and Reconfiguration Manufacturing System is one of the discovery that matches these criteria such as flexibility, reliability and others, the main advantage of RMS is its adoptability to cope up with change in software and hardware configuration for adjusting the promptly. Hence in this paper we have proposed a optimized RMS , the main objective is to reduce the cost of the configuration through task scheduling, we propose Evolutionary algorithm based approach for configuration, moreover here we find the optimal solution through utilizing the machine over the operation set for each machine part, later we find the optimal from the probable assignment. In order to evaluate the algorithm we have performed the case study, a case study shows that Evolutionary algorithm based approach achieves the optimum solution when compared to the existing.
Keywords: RMS, Evolutionary Algorithm, optimal configuration.
Scope of the Article: Advanced Manufacturing Technologies.