• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.865-870
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• 2002

Burn-in is a widely used method to eliminate the initial failures. Preventive maintenance policy such as age replacement is often used in field operation. In this paper burn-in and maintenance policy are taken into consideration at the same time. The properties of the corresponding optimal burn-in times and optimal maintenance policy are discussed.

• Journal of Applied Reliability
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• v.12 no.2
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• pp.57-66
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• 2012

In this paper, we consider the periodic preventive maintenance model for a repairable system following the expiration of replacement-repair warranty. Under this preventive maintenance model, we derive the expressions for the expected cycle length, the expected total cost and the expected cost rate per unit time. Also, we determine the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for Weibull distribution case.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.367-377
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• 2006

This paper develops a periodic preventive maintenance(PM) policy following the expiration of warranty. Two types of warranty are considered: renewing warranty and non-renewing warranty. Also, we consider the situation where each PM cost is an increasing function of the PM effect. We determine the optimal number of PM's before replacing the system by a new one and the optimal length of period for the periodic PM following the expiration of warranty. Explicit solutions to determine the optimal periodic PM are presented for the Weibull distribution case.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.1-9
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• 1988

This paper considers a machine maintenance problem. The machine's condition is partially known by observing the machine's output products. This problem is formulated as an infinite horizon partially observable Markov decison process to find an optimal maintenance policy. However, even though the optimal policy of the model exists, finding the optimal policy is very time consuming. Thus, the intends of this study is to find ${\varepsilon}-optimal$ stationary policy minimizing the expected discounted total cost of the system, ${\varepsilon}-optimal$ policy is found by using a modified version of the well-known policy iteration algorithm. A numerical example is also shown.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.108-116
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• 2010

The maintenance of a deteriorating system is often imperfect. Previous studies have shown that the imperfect preventive maintenance (PM) can reduce the wear out and aging effects of deteriorating systems to a certain level between the conditions of as good as new and as bad as old. In this paper, we employ the concept of the improvement factor in investigating two optimal PM policies; failure limit policy and periodic PM policy. We redefine the improvement factor model as a function of the cost of PM, using this concept, we derive the conditions of optimal PM policies and formulate expressions to compute the expected cost rate. Based on this information, the determination of the maintenance policies which minimize the cost rate is examined. Numerical examples for the Weibull distribution case are also given.

• Journal of Applied Reliability
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• v.11 no.2
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• pp.167-176
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• 2011

This paper introduces models for preventive maintenance policies and considers periodic preventive maintenance policy with minimal repair when the failure of system occurs. It is assumed that minimal repairs do not change the failure rate of the system. The failure rate under prevention maintenance received an effect by a previously prevention maintenance and the slope of failure rate increases the model where it considered. Also the start point of failure rate under prevention maintenance considers the degradation of system and that it increases quotient, it assumed. Per unit time it bought an expectation cost from under this prevention maintenance policy. We obtain the optimal periodic time and the number for the periodic preventive maintenance by using Nakagawa's Algorithm, which minimizes the expected cost per unit time.

• Journal of Applied Reliability
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• v.17 no.3
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• pp.246-255
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• 2017

Purpose: This study proposes the optimal PM (preventive maintenance) policy of leased equipment for lessee's decision-making using two types of reliability condition. Methods: We consider reliability threshold based PM model. Equipment reliability is estimated and used as condition variable. The effect of repair for maintenance is imperfect and represented by age reduction factor. Results: We provide two PM policies. Policy 1 is focused on minimized total cost. This policy guarantees reliability threshold until last maintenance action. Policy 2 focus on maintaining reliability threshold during leased period. The proposed approach provides optimal reliability threshold under number of PM. Through result, we finally construct decision-making process for lessee using reliability threshold and end of reliability. Conclusion: This study provides two PM policy for lessee's decision-making. Through numerical example, we get a result of optimal reliability threshold, number of PM, optimum alternative under lessee's reliability condition.

• Journal of the Korean Operations Research and Management Science Society
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• v.6 no.2
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• pp.7-11
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• 1981

An inspection-maintenance policy is investigated for a system having various states. A policy is characterized by the type of maintenance and the next inspection time. Maintenance actions are classified into various types according to the depth of maintenance. Policy evaluation criterion is the expected cost accumulated up to the failure of the system. The problem is formulated as a Markov decision process and an optimal policy is found by using a policy improvement procedure. A numerical example illustrates the policy for a system having five states.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.41-48
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• 2011

This paper considers the maintenance model suggested by Jung and Park (2010) to adopt the Bayesian approach and obtain an optimal replacement policy following the expiration of NFRRW. As the criteria to determine the optimal maintenance period, we use the expected cost during the life cycle of the system. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach. Also, we describe the revision of uncertainty about parameters in the light of data observed. Some numerical examples are presented for illustrative purpose.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.142-147
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• 2003

Burn-in is a widely used method to eliminate the initial failures. Preventive maintenance policy such as block replacement with minimal repair at failure is often used in field operation. In this, paper burn-in and maintenance policy are taken into consideration at the same time. The cost of a minimal repair is assumed to be a non-decreasing function of its age. The problems of determining optimal burn-in times and optimal maintenance policy are considered.