Ship Preventive Opportunistic Maintenance Strategy  Based on Delay Time Model

Li Ji-hui; Huang Jin-jing; Cui Chun-qiang

doi:10.12052/gdutxb.220118

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Ship Preventive Opportunistic Maintenance Strategy Based on Delay Time Model

更新时间：2026-05-27

- Ship Preventive Opportunistic Maintenance Strategy Based on Delay Time Model
- Vol. 40, Issue 1, Pages: 92-99, 136(2023)
- 作者机构：
  
  湛江科技学院智能制造学院,广东,湛江,524094
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.220118
  CLC： U664.21
- Online First：25 January 2023，
  
  Published：2023
- 稿件说明：
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李冀晖, 黄锦敬, 崔春强. 基于延迟时间模型的船舶预防性机会维修策略[J]. 广东工业大学学报, 2023, 40(1): 92-99, 136.

Li Ji-hui, Huang Jin-jing, Cui Chun-qiang. Ship Preventive Opportunistic Maintenance Strategy Based on Delay Time Model[J]. 2023, 40(1): 92-99, 136.
李冀晖, 黄锦敬, 崔春强. 基于延迟时间模型的船舶预防性机会维修策略[J]. 广东工业大学学报, 2023, 40(1): 92-99, 136. DOI： 10.12052/gdutxb.220118.

Li Ji-hui, Huang Jin-jing, Cui Chun-qiang. Ship Preventive Opportunistic Maintenance Strategy Based on Delay Time Model[J]. 2023, 40(1): 92-99, 136. DOI： 10.12052/gdutxb.220118.

摘要

针对目前船舶关键部件维修不合理导致的维修费用过高、使用率低的问题，提出基于延迟时间理论的船舶关键部件预防性维修策略。该策略以各部件的定期检测为基础，根据缺陷阶段和故障阶段的不同特点，将各部件维修分为检测维修和延迟维修，在延迟阶段引入机会维修思想，建立了船舶关键部件机会维修模型。根据部件检测维修记录和故障数据，运用极大似然估计法估计模型参数。以检测周期和延迟时间为优化变量，以最小费用率为优化目标，得到长期使用下的船舶关键部件机会维修策略。研究结果表明，与单纯的检测维修策略和传统的预防性维修方法相比，该策略能有效降低船舶维修费用，减少停机维修次数，提高船舶的使用效率，为船舶维修提供决策依据和参考。

Abstract

A preventive maintenance strategy for key components of ships is advanced based on the delay time theory. This strategy aims at the problem of high maintenance cost and low utilization rate caused by unreasonable maintenance of key parts. It bases on periodic inspection of each component

and divides the maintenance of each component into inspection maintenance and delay maintenance according to the different characteristics of defect and failure stage. And the idea of opportunity maintenance is introduced in the delay phase

to establish an opportunistic maintenance model for the ship’s key components. According to this strategy

the opportunistic maintenance strategy of the key parts under long-term use can be obtained in four steps: Base on component failure data and inspection maintenance records. Estimate model parameters by maximum likelihood estimation. Take detection cycle and delay time as optimization variables. Take the minimum cost ratio as the optimization objective. The result of this research indicates that this strategy can more effectively reduce the cost of ship maintenance

reduce downtime for maintenance

improve the efficiency of the use of the ship

and provide a decision basis and reference for ship maintenance

than the simple test maintenance strategy and traditional preventive maintenance method.

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Keywords

references

王子睿. 基于状态的船舶动力系统维修时机决策研究[D]. 武汉: 武汉理工大学, 2016.

GIORGIO M, GUIDA M, PULCINI G. A wear model for assessing the reliability of cylinder liners in marine diesel engines [J]. IEEE Transactions on Reliability, 2007, 56(1): 158-166.

HERMANN S, RUGGERI F. Modeling wear in cylinder liners [J]. Quality and Reliability Engineering International, 2017, 33(4): 839-851.

YANG L Q, ZHAO J L, LI G. Condition-based maintenance strategy for critical components of ships based on performance degradation [J]. Journal of Harbin Engineering University, 2020, 41(4): 613-618.

SUN L K, GENG J B, JIN J S, et al . Preventive maintenance strategy of ship based on variable period [J ] . Ship Ocean Engineering, 2009, 38(1): 97-100.

LI J H, HUANG J J, WEI F Q. Ship state opportunity maintenance strategy based on proportional hazard model [J]. Journal of Guangdong Ocean University, 2021, 41(5): 122-129.

CHRISTER A H, WALLER W M. Delay time models of industrial inspection maintenance problems [J]. Journal of The Operational Research Society, 1984, 35(5): 401-406.

KERRES B, FISCHER K, MADLENER R. Economic evaluation of maintenance strategies for wind turbines: a stochastic analysis [J]. IET Renewable Power Generation, 2015, 9(7): 766-774.

WANG W, CHRISTER A H. Solution algorithms for a nonhomogeneous multi-component inspection model [J]. Computers Operations Research, 2003, 30(1): 19-34.

JONES B, JENKINSON I, WANG J. Methodology of using delay-time analysis for a manufacturing industry [J]. Reliability Engineering and System Safety, 2009, 94(1): 111-124.

JONES B, JENKINSON I, YANG Z, et al . The use of Bayesian network modeling for maintenance planning in a manufacturing industry [J ] . Reliability Engineering and System Safety, 2010(95): 267-277.

LYU W Y, ZHENG R. Delay-time-based model of optimization grouping maintenance type and case study [J]. Systems Engineering-Theory Practice, 2013, 33(7): 1654-1660.

HU H J, CHENG G X, DUAN Q, et al . Delay time model based on imperfect maintenance [J ] . Journal of Xi’an Jiaotong University, 2009, 43(6): 103-107.

LIU G H, CHEN S K, JIN H, et al . Optimum imperfect inspection and maintenance scheduling model considering delay time theory [J ] . Journal of Zhejiang University (Engineering Science) , 2020, 54(7): 1298-1307.

WANG W. An overview of the recent advances in delay-time-based maintenancemodeling [J]. Reliability Engineering System Safety, 2012, 106(5): 165-178.

LI X, ZHU C C, LI Y, et al . Maintenance strategy of wind turbine based on the delay time model [J ] . Journal of Chongqing University, 2020, 43(10): 20-28.

BAI W H, ZUO H F, LYU D F, et al . Maintenance optimization method of civil aircraft based on delay time mode [J ] . Journal of Nanjing University of Aeronautics Astronautics, 2015, 47(6): 890-896.

ZHAO H S, YAN S T, LIU J Q. Optimization maintenance of wind turbines based on opportunistic maintenance model [J]. Power System and Clean Energy, 2012, 28(7): 1-5.

HE D Q, LUO A, DENG J X, et al . Optimization model of preventive maintenance decision-making for train bogie key components [J ] . Computer Integrated Manufacturing Systems, 2018, 24(5): 1155-1161.

WANG L, HU H, WANG Y, et al . The availability model and parameters estimation method for the delay time model with imperfect maintenance at inspection [J ] . Applied Mathematical Modelling, 2011, 35(6): 2855-2863.

温正, 孙华克. MATLAB智能算法[M]. 北京: 清华大学出版社, 2017: 145-196.

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