A fuzzy linear programming approach to layout design of dynamic cellular manufacturing systems with route selection and cell reconfiguration

Abstract

This paper presents a novel integer non-linear programming model for the layout design of dynamic cellular manufacturing systems (DCMS) under an uncertain environment. A novel aspect of this model is concurrently making the interrelated cell formation and intracell layout decisions in a dynamic and uncertain environment. Other compromising aspects are: considering single-row layout of equal area facilities to locate machines in each cell, machine relocation based on locations assigned to a machine during two successive periods, calculation of material handling cost based on the distance between the locations assigned to machines, and presenting the existence of uncertainty in the model parameters by fuzzy numbers. Such an integrated model with an extensive coverage of important manufacturing features has not been proposed before and incorporates several design features including intracell layout, operation sequence, operation time, alternative process routing, duplicate machines, machine capacity, route selection, production volume of parts and cell reconfiguration. The uncertainty stems from part demand fluctuation and machine capacity. Linearization procedures are used to transform the proposed non-linear programming model into a linearized formulation. Finally, a new fuzzy linear programming approach which can consider the fuzziness of whole parameters in a mathematical model is developed to solve the linearized model. A comprehensive example is solved by the Lingo software to verify the performance of the proposed model and developed fuzzy approach. Also, the computational results show that the proposed model to some extent overcomes common disadvantages in the existing dynamic cell formation models that have not yet considered layout problems and fuzzy issues.