Optimal control and simulation for production planning of network failure-prone manufacturing systems with perishable goods

The problem of controlling the production rates of failure prone manufacturing systems has stochastic features that make it more complex and challenging. In this study, we consider a network of manufacturing machines based on the hedging point policy where the final goods are perishable, and the demand rate is constant. Our objective in this paper is to control the production rates of multiple machines in failure prone manufacturing systems in the presence of perishable goods in order to minimise the expected cost consisting of holding, shortage, perished goods and repair costs over an infinite horizon. We develop a new framework by way of a simulation-optimisation approach to deal with complexity and uncertainty. To this end, we first formulate the analytical model subject to stochastic failures and corrective repairs. Then, we use a combination of simulated annealing metaheuristic, simulation and Taguchi experimental design to estimate the optimal control policy. In addition, a numerical example is presented to illustrate the applicability and efficacy of the proposed framework.