TY - JOUR
T1 - Joint optimization of condition-based production and maintenance with mutual production-deterioration dependencies
AU - Zhang, Hanxiao
AU - Wang, Zhe
AU - Liu, Xingchen
AU - Gaudoin, Olivier
AU - Xie, Min
PY - 2025/4
Y1 - 2025/4
N2 - Production control and maintenance scheduling are the two major cost-effective methodologies in the manufacturing systems. The existing literature considers these processes in isolation or with unidirectional dependencies. To fill this gap, we propose an integrated control model of maintenance and production process considering the mutual influence between production and deterioration in a single-machine system. By leveraging condition monitoring data, we enhance decision-making effectiveness and develop a comprehensive framework based on an infinite-horizon Markov decision process. We establish and prove the monotonic structural properties of total profit and maintenance actions relative to machine state, and develop an improved value iteration algorithm to reduce the computational space. Numerical experiments demonstrate the performance of our model in maximizing profits compared to traditional condition-based maintenance and condition-based production approaches. Sensitivity analysis further highlights key parameters influencing optimal policies, providing valuable insights for practical applications. © 2024 Elsevier Ltd.
AB - Production control and maintenance scheduling are the two major cost-effective methodologies in the manufacturing systems. The existing literature considers these processes in isolation or with unidirectional dependencies. To fill this gap, we propose an integrated control model of maintenance and production process considering the mutual influence between production and deterioration in a single-machine system. By leveraging condition monitoring data, we enhance decision-making effectiveness and develop a comprehensive framework based on an infinite-horizon Markov decision process. We establish and prove the monotonic structural properties of total profit and maintenance actions relative to machine state, and develop an improved value iteration algorithm to reduce the computational space. Numerical experiments demonstrate the performance of our model in maximizing profits compared to traditional condition-based maintenance and condition-based production approaches. Sensitivity analysis further highlights key parameters influencing optimal policies, providing valuable insights for practical applications. © 2024 Elsevier Ltd.
KW - Condition monitoring
KW - Condition-based maintenance
KW - Condition-based production
KW - Reliability
UR - http://www.scopus.com/inward/record.url?scp=85210686386&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85210686386&origin=recordpage
U2 - 10.1016/j.ress.2024.110679
DO - 10.1016/j.ress.2024.110679
M3 - RGC 21 - Publication in refereed journal
SN - 0951-8320
VL - 256
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 110679
ER -