Investigating the effect of input variables on the performance of FMS followed by multi-response optimization: A simulation study

Abstract

Flexible manufacturing systems (FMSs) help in producing reliable and good-quality products. The performance of FMSs depends on the various input variables and therefore, it is important to investigate their effect on the performance of the system. This work explores the effect of three input variables i.e., newly developed sequencing rules (SR), the number of machines, and AGV selection rules to determine their optimal setting that yields optimal results of three performance measures viz. makespan time, AGV utilization, and machine utilization simultaneously. ARENA simulation software was used to develop a replicate model of an FMS problem taken from literature. Nine models for a different combination of variables as input as per Taguchi’s L9 orthogonal array were developed and data for three performance measures were collected. Further, multi-response optimization using the integrated MEREC-MARCOS method was performed. The results of the study revealed that considering 3 machines, with GMPD as SR and shortest distance as AGV selection rule yields the optimal performance of the FMS. Further, among the three input variables, the number of machines was found to have a significant effect on the multi-performance measures. Finally, the optimal solution obtained in the study was validated by performing a confirmation test.