Optimization–simulation–optimization based approach for proactive variation reduction in assembly

This paper addresses the economic benefits of selectively assigning a batch of subassemblies to each other after inspecting and correcting them as needed. Our work is based on optimizing the collective cost of subassembly inspection, rework, scrap, final assembly failure, and the act of subassembly mating. The expected value for the cost is estimated using Monte Carlo Simulation and optimized using a metaheuristic. After each simulation replication where we simulate a batch of subassemblies, we assign the inspected subassembly parts so that the rolled yield throughput is maximized. The complexity of this work is attributed to the fact that we solve an optimization problem for an objective that is estimated using simulation, and in each simulation replication there is another optimization problem to be solved for selective assembly. Significant improvements in assembly lines are predicted to be accomplished when this work is integrated in a real production environment.