Optimal Lot Sizing with Scrap and Random Breakdown Occurring in Backorder Replenishing Period

This paper is concerned with determination of optimal lot size for an economic production quantity model with scrap and random breakdown occurring in backorder replenishing period. In most real-life manufacturing systems, generation of defective items and random breakdown of production equipment are inevitable. To deal with the stochastic machine failures, production planners practically calculate the mean time between failures (MTBF) and establish the robust plan accordingly, in terms of optimal lot size that minimizes total production-inventory costs for such an unreliable system. Random scrap rate is considered in this study, and breakdown is assumed to occur in the backorder filling period. Mathematical modeling and analysis is used and the renewal reward theorem is employed to cope with the variable cycle length. An optimal manufacturing lot size that minimizes the long-run average costs for such an imperfect system is derived. Numerical example is provided to demonstrate its practical usages.