PERFORMANCE OF PRODUCTION CELLS WITH SCRAP AND REWORKS: ANALYTICAL AND SIMULATION APPROACH

This study proposes an analytical framework for evaluating manufacturing systems subject to random failures and quality disruptions, where each defective part may be scrapped or reworked for a specific number of times. System behaviour is modelled using a discrete-time Markov chain, allowing the derivation of several key performance indicators (KPIs) including throughput, efficiency, yield, and the required raw material. A simulation model complements the analytical approach, validating the results and offering deeper insights into system behaviour. The close agreement between simulation and analytical results confirms the model’s accuracy, with negligible errors across diverse scenarios considering discrete and continuous distributions of the system lifetimes and repairs. The present research also demonstrates that, in contrast to the majority of studies in the literature, which estimate the quality rate by the yield, this substitution results in a significant overestimation of the system throughput by up to 25 %, which has severe effects on budgeting, production planning, and customer satisfaction.