A Fuzzy Logic Decision Support Algorithm for Multi-cell Flexible Manufacturing Systems

Because of the nature of conventional 0-1 part-family incidence matrix, a multi-cell flexible manufacturing systems (MCFMS) using conventional part-family formation algorithms, such as array-based clustering, similarity coefficient-based clustering, and mathematical programming, in a cellular manufacturing mode can assign a part family only to one machine cell. The consequence is that each part type has a fixed route through the system. When each part family is limited to a fixed route through the system, the performance of an MCFMS is diminished. This is because the inherent flexibility of the MCFMS is not fully utilized. This research proposes a fuzzy dynamic routing method that applies a fuzzy clustering algorithm combined with a certainty factor procedure to suggest the favorable route in an MCFMS. Computational simulations show that the proposed dynamic routing method that seeks to balance workload in an MCFMS is more effective than the fixed routing method in reducing mean flowtime, mean tardiness, and mean absolute lateness, in an environment characterized by high system utilization (85% or higher) and under a variety of demand patterns and machine breakdowns.