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Combinatorial optimization for the configuration of workforce and equipment in reconfigurable assembly lines

Abstract : Mass customization and frequent market fluctuations push industrial companies to employ flexible and reconfigurable multi/mixed-model assembly lines instead of dedicated ones. This thesis focuses on this problem. It concentrates mainly on mixed-model assembly line design and balancing problems. The questions concerning the efficiency of such lines, the importance of optimal task assignment and use of walking workers are asked and studied. To increase the flexibility of the line, we account for different types of task assignments: fixed, model-dependent,and dynamic. We aim to design a line that can handle various entering product models. We use combinatorial optimization methods, and,in particular, robust optimization approaches. We present an extensive literature review on line balancing, workforce planning, and workforce reconfiguration strategies in different production systems. The first problem addresses a configuration selection problem between a single multi-model line and multiple dedicated lines. The second problem consists in designing and balancing a mixed-model assembly line with walking workers. We propose fixed and model-dependent task assignments for a given set of product mixes. The goal is to minimize the total cost of workers and equipment for the worst case. The third problem extends the second one. It considers the dynamic task assignment. In the last problem, we extend the third problem for the case where the sequence of products unfolds takt by takt. In this context, we minimize both the expected total cost and the worst-case cost. In order to solve the considered problems, we develop several exact methods and heuristics: mixed-integer linear programming models, greedy algorithm, local search,matheuristic and fixed-and-optimize heuristics among others. We also apply a Markov Decision Process to the proposed line balancing problem in the last chapter. It is the first study applying this method to a line balancing problem. Computational experiments evaluate the performance of the proposed approaches in terms of solution quality and time consumption. We draw managerial insights in each chapter. Our results show the superiority of the dynamic task assignment compared to model-dependent and fixed ones in different production situations.
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Submitted on : Tuesday, January 11, 2022 - 12:37:08 PM
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  • HAL Id : tel-03520980, version 1

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Seyyed Ehsan Hashemi Petroodi. Combinatorial optimization for the configuration of workforce and equipment in reconfigurable assembly lines. Operations Research [cs.RO]. Ecole nationale supérieure Mines-Télécom Atlantique, 2021. English. ⟨NNT : 2021IMTA0266⟩. ⟨tel-03520980⟩

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