Design of reconfigurable flow lines using MOPSO and maximum deviation theory

Abstract

Reconfigurable manufacturing system (RMS) is a state-of-the-art technology, which offers the exact capacity and functionality needed, through rapid and cost-effective reconfigurations in its modular structure. The reconfigurable machine tools (RMTs) can perform a variety of operations in its existing configuration and can further be reconfigured to change the operational capabilities. Thus, the selection of a machine configuration plays a vital role not only in the cost-effectiveness but in the future reconfiguration effort requirements. In the present study, authors have attempted a multiple-objective optimization of RMS flow line configuration, taking the cost, machine utilization, operational capability, and configuration convertibility as the conflicting objectives. The cost and machine utilization represent the economic justification while the operational capability and the configuration convertibility portray the ability of rapid and cost-effective reconfiguration ability. The emphasis of this research is to design the economic RMS configuration, which can rapidly and cost-effectively respond to the volatile market conditions. Multiple-objective particle swarm optimization (MOPSO) has been implemented to handle the discrete and discontinuous search space. The large number of Pareto frontiers is further ranked to avoid subjectiveness and imprecision in the decision making, based on the composite scores obtained through maximum deviation theory. A numerical illustration is presented to illustrate the developed methodology of reconfigurable flow line configuration design.