FMS design model with multiple objectives using compromise programming

There has been a great change in manufacturing systems toward computer-controlled flexible manufacturing systems (FMS). The design and operation of the FMS involve intricate and interconnected decisions that result in the maximum performance of the system. However, the design and operational decisions have been made separately in consideration of a single-system performance measure. This paper presents a method for simultaneously determining design and control parameters of an FMS with the multiple performance objectives via full-factorial design of experiments, regression analysis and compromise programming. For a numerical example, the SIMAN simulator models a hypothetical FMS with six workstations. Eight design and control parameters are simultaneously determined by compromising four performance measures that are formulated using regression analysis.