Condition based maintenance in the context of opportunistic maintenance

Koochaki, J.; Bokhorst, Jos; Wortmann, Hans; Klingenberg, W.

doi:10.1080/00207543.2011.636924

Cited by 104 publications

(53 citation statements)

References 23 publications

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“…If the hazards functions of the other units exceed d 2 then opportunistic maintenance will be performed on those units as well. More related papers for multi-unit systems using PHM can be found in Marseguerra et al (2002), Barata et al (2002), Castanier et al (2005), Saunil et al (2009), and Koochaki et al (2012).…”

Section: Introductionmentioning

confidence: 99%

Joint optimization of maintenance policy and inspection interval for a multi-unit series system using proportional hazards model

Jafari

Naderkhani

Makiš

2017

Journal of the Operational Research Society

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Unlike the previous maintenance models of multi-unit systems which considered condition-based maintenance (CBM) or age information separately, we propose a novel optimization model which is characterized by a combination of CBM and age information using proportional hazards model. The preventive maintenance is applied for the main two units, where one unit is the core part of the system and subject to CM, and only the age information for the second main unit is available. Also, the other units are adjusted or replaced each time when the system is maintained. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process framework. The formula for the mean residual life of the system is derived, which is an important statistic in practical applications. A practical example of a multi-unit system from a mining company is provided, and a comparison with other policies shows an outstanding performance of the new model and the control policy proposed in this paper.

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Section: Introductionmentioning

confidence: 99%

Joint optimization of maintenance policy and inspection interval for a multi-unit series system using proportional hazards model

Jafari

Naderkhani

Makiš

2017

Journal of the Operational Research Society

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“…Jhang and Sheu [18]; Okamura and Dohi [26]) to a greater (Satow and Osaki [29]), or lesser extent (Badía and Berrade [3]). Additional references to opportunistic maintenance can be found in [16] and [19].…”

Section: Introductionmentioning

confidence: 99%

A study of postponed replacement in a delay time model

Berrade

Scarf

Cavalcante

2017

Reliability Engineering & System Safety

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We develop a delay time model for a one component system with postponed replacement to analyze situations in which maintenance might not be executed immediately upon discovery of a defect in the system. Reasons for postponement are numerous: to avoid production disruption or unnecessary or ineffective replacement; to prepare for replacement; to extend component life; to wait for an opportunity. This paper explores conditions that make postponement cost-effective. We are interested in modelling the reality in which a maintainer either prioritizes functional continuity or is not confident of the inspection test indicating a defective state. In some cases more frequent inspection and a longer time limit for postponement are recommended to take advantage of maintenance opportunities, characterized by their low cost, arising after a positive inspection. However, when the cost of failure increases, a significant reduction in the time limit of postponement interval is observed. The examples reveal that both the time to defect arrival and delay time have a significant effect upon the cost-effectiveness of maintenance at the limit of postponement. Also, more simply, we find that opportunities must occur frequently enough and inspection should be a high quality procedure to risk postponement.

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“…They considered a system composed by three components mounted in series and varied few elements such as the number of components, the length of the opportunistic zone and used a dynamic grouping in which group maintenance activity is carried out only for the non-failed components that are in the opportunistic zone. Koochaki et al [14] developed a group maintenance policy for parallel machines. Their model allows determining jointly the optimal maintenance frequencies, the optimal positions of the maintenance activities and the optimal job sequence.…”

Section: Introductionmentioning

confidence: 99%

Jointly Production and Correlated Maintenance Optimization for Parallel Leased Machines

2017

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This paper deals with a preventive maintenance strategy optimization correlated to production for a manufacturing system made by several parallel machines under lease contract. In order to minimize the total cost of production and maintenance by reducing the production system interruptions due to maintenance activities, a correlated group preventive maintenance policy is developed using the gravity center approach (GCA). The aim of this study is to determine an economical production plan and an optimal group preventive maintenance interval T n at which all machines are maintained simultaneously. An analytical correlation between failure rate of machines and production level is considered and the impact of the preventive maintenance policy on the production plan is studied. Finally, the proposed maintenance policy GPM is compared with an individual simple strategy approach IPM in order to illustrate its efficiency.

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Condition based maintenance in the context of opportunistic maintenance

Cited by 104 publications

References 23 publications

Joint optimization of maintenance policy and inspection interval for a multi-unit series system using proportional hazards model

Joint optimization of maintenance policy and inspection interval for a multi-unit series system using proportional hazards model

A study of postponed replacement in a delay time model

Jointly Production and Correlated Maintenance Optimization for Parallel Leased Machines

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