Condition-based maintenance policy for accelerated degradation production equipment considering imperfect maintenance

Under the constraint of manufacturer-defined preventive maintenance thresholds, this study considers the effects of equipment degradation on production equipment failure and product quality, and proposes a condition-based maintenance (CBM) policy for accelerated degradation production equipment due to imperfect maintenance with the objective of minimizing the average cost rate. The proposed CBM policy incorporates a non-fixed-period inspection plan and a preventive replacement policy. To prevent premature equipment failure, the inspection period for each maintenance cycle depends on the degradation rate and initial degradation state of each maintenance cycle. Moreover, in order to reduce the maintenance costs, including the preventive maintenance (PM) cost of the equipment and the repair cost of defective items, a threshold value for the number of imperfect preventive maintenance actions is set for timely preventive replacement of equipment. Finally, a numerical example is provided to verify the feasibility and effectiveness of the proposed CBM policy.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
Published
2026-11-11
DOI
https://doi.org/10.1177/1748006x261504272
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Condition-based maintenance policy for accelerated degradation production equipment considering imperfect maintenance

Jinlong Yu, Yuanpeng Ruan, Xianghai Ding, Xiang Liu
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
Reliability and Maintenance Optimization
article

Condition-based maintenance policy for accelerated degradation production equipment considering imperfect maintenance

Jinlong Yu, Yuanpeng Ruan, Xianghai Ding, Xiang Liu
article en

Abstract

Under the constraint of manufacturer-defined preventive maintenance thresholds, this study considers the effects of equipment degradation on production equipment failure and product quality, and proposes a condition-based maintenance (CBM) policy for accelerated degradation production equipment due to imperfect maintenance with the objective of minimizing the average cost rate. The proposed CBM policy incorporates a non-fixed-period inspection plan and a preventive replacement policy. To prevent premature equipment failure, the inspection period for each maintenance cycle depends on the degradation rate and initial degradation state of each maintenance cycle. Moreover, in order to reduce the maintenance costs, including the preventive maintenance (PM) cost of the equipment and the repair cost of defective items, a threshold value for the number of imperfect preventive maintenance actions is set for timely preventive replacement of equipment. Finally, a numerical example is provided to verify the feasibility and effectiveness of the proposed CBM policy.

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
Hangzhou Dianzi University (CN)
Reliability and Maintenance Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Condition-based maintenance policy for accelerated degradation production equipment considering imperfect maintenance — Jinlong Yu, Yuanpeng Ruan, et al. · Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability (2026) | TGRS Research Map | TGRS