Condition-based production: Maximizing manufacturing revenue considering failure risk and reject rates

Optimizing productivity in manufacturing is crucial for increasing output and reducing costs; however, it can also negatively impact product quality and accelerate system degradation. This study is the first to propose a method for dynamically adjusting productivity while considering both system degradation and product quality. We construct a dynamic programming model using optimal control theory to address both fixed maintenance cycles and the joint optimization of production and maintenance strategies. Our approach identifies optimal production strategies for various scenarios, showing that integrating product quality considerations with productivity and degradation significantly enhances overall outcomes. Extensive numerical studies validate our results, demonstrating that this comprehensive optimization scheme not only increases production system revenue but also reduces maintenance costs as well as product defects. By accounting for the dual impact of productivity on system degradation and product quality, this research provides a more holistic and practical strategy for maximizing manufacturing revenue and product reliability. The findings offer significant theoretical and practical value, guiding enterprises toward achieving a balance between high productivity, system longevity, and product quality.