Moment recursions of the cumulative performance of production systems using discrete-time Markov reward models

Uses discrete-time Markov reward models to obtain moment recursions of the cumulative performance of an automated manufacturing system (AMS). AMS exists in various structure states due to failures, repairs and reconfigurations of its components. This multi-state behavior is modeled using a Markov reward structure that is similar to the continuous-time versions. This methodology may also be used to compute other performance measures, such as the expected in-process inventory and the expected production per unit time. A three-stage transfer line with finite buffers is used to illustrate the methods obtained in the paper