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Cellular Manufacturing is a member of modern production methods. In general, design of Cellular Manufacturing Systems (CMS) consists of three decision stages: (1) formation of cells and product groups, (2) layout of cells on the shop floor (inter-cell layout), (3) layout of machines within the cells (intra-cell layout). For a successful CMS design, these decisions should be taken concurrently. In this study, firstly we propose a linear mixed-integer mathematical programming model for the expression of a multi period (dynamic) CMS design problem. The model determines cell formations, product routings, material flows, inter-cell and intra-cell layout. It considers operations sequences of products, alternative product routings, lot splitting, duplicated machines, machine purchasing and removal, dynamic reconfiguration of cells and machines, inter-cell and intra-cell material handling costs, operation costs and durations of products, capacities of machinery and material handling devices. Due to the complexity of the problem we propose a Linear Programming embedded Simulated Annealing method. Several problems from the literature are found and solved for the testing of the method., Computer and Industrial Engineering;et al.;Gaziantep University;Istanbul Commercial University;Journal of Intelligent Manufacturing Systems;Sakarya University, Department of Industrial Engineering

Cellular Manufacturing is a member of modern production methods. In general, design of Cellular Manufacturing Systems (CMS) consists of three decision stages: (1) formation of cells and product groups, (2) layout of cells on the shop floor (inter-cell layout), (3) layout of machines within the cells (intra-cell layout). For a successful CMS design, these decisions should be taken concurrently. In this study, firstly we propose a linear mixed-integer mathematical programming model for the expression of a multi period (dynamic) CMS design problem. The model determines cell formations, product routings, material flows, inter-cell and intra-cell layout. It considers operations sequences of products, alternative product routings, lot splitting, duplicated machines, machine purchasing and removal, dynamic reconfiguration of cells and machines, inter-cell and intra-cell material handling costs, operation costs and durations of products, capacities of machinery and material handling devices. Due to the complexity of the problem we propose a Linear Programming embedded Simulated Annealing method. Several problems from the literature are found and solved for the testing of the method., Computer and Industrial Engineering;et al.;Gaziantep University;Istanbul Commercial University;Journal of Intelligent Manufacturing Systems;Sakarya University, Department of Industrial Engineering