Optimal Allocation of Work in Assembly Systems
研究随机装配系统中如何分配工作以最大化产出率，发现应向组件工站分配更多工作、向装配工站分配更少工作，且并行度越高改进空间越大。
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.