Design of robust cellular manufacturing system for dynamic part population considering multiple processing routes using genetic algorithm |
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| Affiliation: | 1. Department of Mechanical Engineering, Guru Jambheshwar University of Science & Technology, Hisar, HR, India;2. Department of Mechanical Engineering, Sant Longowal Institute of Engineering & Technology, Longowal, PB, India;1. School of Management, Hangzhou Dianzi University, Hangzhou 310018, PR China;2. Department of Mathematics, China Jiliang University, Hangzhou 310018, PR China;3. Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA;1. Faculty of Integrated Technologies, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong, BE1410, Brunei Darussalam;2. Department of Industrial Engineering, King Abdulaziz University, Abdullah Suleyman Road, Jeddah, 21589, Saudi Arabia;1. Department of Industrial & Systems Engineering, University of Ohio, Athens, OH, USA;2. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran;3. Research Center for Organizational Processes Improvement, Sari, Iran;4. Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran;5. Department of Electrical Engineering, University of North Carolina at Charlotte, Charlotte, NC, USA;1. School of Industrial & Systems Engineering, College of Engineering, University of Tehran, Tehran, P.O. Box 11155-4563, Iran;2. Department of Industrial Engineering, Faculty of Engineering, College of Farabi, University of Tehran, Iran;3. Graduate School of Management and Econimics, Sharif University of Technology, Tehran, Iran |
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| Abstract: | In this paper, a comprehensive mathematical model is proposed for designing robust machine cells for dynamic part production. The proposed model incorporates machine cell configuration design problem bridged with the machines allocation problem, the dynamic production problem and the part routing problem. Multiple process plans for each part and alternatives process routes for each of those plans are considered. The design of robust cell configurations is based on the selected best part process route from user specified multiple process routes for each part type considering average product demand during the planning horizon. The dynamic part demand can be satisfied from internal production having limited capacity and/or through subcontracting part operation without affecting the machine cell configuration in successive period segments of the planning horizon. A genetic algorithm based heuristic is proposed to solve the model for minimization of the overall cost considering various manufacturing aspects such as production volume, multiple process route, machine capacity, material handling and subcontracting part operation. |
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| Keywords: | Cellular manufacturing Robust design Multiple process-routes Subcontracting part operation Genetic algorithm |
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