Improving repetitive manufacturing systems: Model and insights

We consider a manufacturing system that is controlled by a fixed-cycle smoo thed production policy. This policy, which is becoming increasingly common in repetitive manufacturing environments, is characterized by a production rate that is updated on a periodic basis. We model the system as a stochast ic process that includes parameters for vendor responsiveness, plant respon siveness, randomness in production yield rates, nonstationarity and randomn ess in market demand, demand forecast error, operating cost rates, and safe ty stock. Properties of the model expose structural relationships between e xpected system performance and system parameters.