Performance analysis of stochastic flow lines with limited material supply

In order to improve the performance of production systems, companies consider the optimization of the flow line configuration. However, the material supply of the flow line exerts a strong influence on the output of the production system since material shortages impede the flow of workpieces through the flow line. Simultaneously, the configuration of the flow line determines the demand for material. Consequently, the mutual interdependence between the material supply and the flow line has to be considered in order to balance a sufficient material supply of the flow line avoiding material shortages as well as excessive material inventory and handling effort. We provide integrated approaches for the evaluation and optimization of stochastic flow lines with limited material supply. Thereby, we make use of several evaluation methods as Markov chain approaches, aggregation and decomposition approaches as well as linear programming. Further, we model open and closed queuing networks in continuous and discrete time. Hence, we present exact and approximate approaches that allow us to study the effects in several stochastic production systems with limited material supply. In order to improve the performance of production systems, companies consider the optimization of the flow line configuration. However, the material supply of the flow line exerts a strong influence on the output of the production system since material shortages impede the flow of workpieces through the flow line. Simultaneously, the configuration of the flow line determines the demand for material. Consequently, the mutual interdependence between the material supply and the flow line has to be considered in order to balance a sufficient material supply of the flow line avoiding material shortages as well as excessive material inventory and handling effort. We provide integrated approaches for the evaluation and optimization of stochastic flow lines with limited material supply. Thereby, we make use of several evaluation methods as Markov chain approaches, aggregation and decomposition approaches as well as linear programming. Further, we model open and closed queuing networks in continuous and discrete time. Hence, we present exact and approximate approaches that allow us to study the effects in several stochastic production systems with limited material supply.