Simulation-Based Production Process Improvement Considering the Quality-Cost Trade-Off

Abstract

Production systems are increasingly required to maintain high quality standards while simultaneously reducing operational costs and ensuring production efficiency. This study presents a simulation-based approach to production process improvement considering the quality–cost trade-off. The main objective of the research was to develop a decision-support framework enabling the analysis of how processing time and repair policies influence production system performance under varying operational conditions. A discrete-event simulation model was developed in the FlexSim environment to represent selected stages of a manufacturing process, including processing operations, quality inspection, and rework activities for nonconforming products. The proposed approach incorporates the relationship between processing time and product quality, enabling the evaluation of multiple production scenarios characterized by different operational strategies and repair limits. The study applies a multi-criteria analysis focused on balancing quality-related outcomes and operational profitability. Simulation results were evaluated using Pareto-based analysis to identify efficient production configurations characterized by different levels of product quality, production cost, and economic performance. The obtained results indicate that extending processing time may improve product conformity; however, it can simultaneously reduce operational efficiency and increase production costs. Moreover, excessive rework intensity does not necessarily generate proportional economic benefits. The proposed approach may support managerial decision-making in manufacturing systems by enabling the identification of production strategies adapted to different quality and cost priorities.