Optimal Allocation of Work in Assembly Systems

We investigate how to allocate work in stochastic assembly systems so as to maximize throughput. We use Markov models for systems with exponential processing times and simulation-based methods for other probability distributions. We find that assembly systems should be unbalanced in the direction of assigning less work to assembly and more to component stations. We also find that greater parallelism offers greater opportunity for improvement.