a comprehensive mathematical model for the design of a dynamic cellular manufacturing system integrated with production planning and several manufacturing attributes

dynamic cellular manufacturing systems,   mixed-integer non-linear programming,   production planning, manufacturing attributes   this paper presents a novel mixed-integer non-linear programming model for the design of a dynamic cellular manufacturing system (dcms) based on production planning (pp) decisions and several manufacturing attributes. such an integrated dcms model with an extensive coverage of important design features has not been proposed yet and incorporates several manufacturing attributes including alternative process routings, operation sequence, processing time, production volume of parts, purchasing machine, duplicate machines, machine depot, machine capacity, lot splitting, material flow conservation equations, inflation coefficient, cell workload balancing, budget constraints for cell construction and machine procurement, varying number of formed cells, worker capacity, holding inventories and backorders, outsourcing part-operations, warehouse capacity, and cell reconfiguration. the objective of the integrated model is to minimize the total costs of cell construction, cell unemployment, machine overhead and machine processing, part-operations setup and production, outsourcing, backorders, inventory holding, material handling between system and warehouse, intra-cell and inter-cell movements, purchasing new machines, and machine relocation/installation/uninstallation. a comprehensive numerical example taken from the literature is solved by the lingo software to illustrate the performance of the proposed model in handling the pp decisions and to investigate the incorporated manufacturing attributes in an integrated dcms .