Integrated operation planning and process adjustment for optimum cost with attention to manufacturing quality and waste

Operation planning and process adjustment are two important aspects of manufacturing operations that can have a significant impact on the performance of a manufacturing system. A framework is proposed for integrating these two planning activities to improve product quality as well as cost and waste minimization. Traditional models for quality, cost, and waste management have two shortcomings: i) they fail to connect to the root cause of the problem - process variation, and ii) operation planning and process adjustment are either ignored or optimized separately. The proposed model responds to these two shortcomings. Objectives relating to product quality and waste are incorporated into a model for unit product cost. A statistical analysis model is built to consider the stack-up of variation from individual processes into the assembled product. Based on this statistical analysis model, controllable variables associated with operation planning and process adjustment are optimized using a gradient-based method. The effectiveness of this framework is demonstrated through a case study; Monte Carlo simulations are employed to validate the accuracy of the proposed approach (the error rate between the analytical result and the simulation result is less than 0.1%). The proposed model is also compared to a method from the literature. It is shown that a better accuracy and a lower cost are achieved with the proposed model (the error rate of the proposed model is less than 10% of that of the existing model). This paper highlights the importance of jointly considering operation planning and process adjustment in quality applications and provides practical insights for manufacturers to improve product quality and reduce production costs through operation planning and process adjustment.