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

Xiaolei Lv, Liangxing Shi, Yingdong He and Zhen He

European Journal of Operational Research, 2025, vol. 327, issue 1, 218-231

Abstract: 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.

Keywords: Optimal production control; Joint production and maintenance; HAMILTONIAN function; Operational decision-making; Product quality (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221725003534
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:327:y:2025:i:1:p:218-231

DOI: 10.1016/j.ejor.2025.04.051

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().