• 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.31 no.3
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• pp.193-204
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• 2003

In this paper, we consider a periodic preventive maintenance(PM) policy in which each PM reduces the hazard rate but remains the pattern of hazard rate unchanged. And the system undergoes only minimal repairs at failures between PM's. The expected cost rate per unit time is obtained. The optimal number N of PM and the optimal period x, which minimize the expected cost rate per unit time are discussed. Explicit solutions for the optimal periodic PM are given for the Weibull distribution case.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.2
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• pp.91-93
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• 1978

A methodology which can be employed to obtain an optimal preventive maintenance policy that maximizes the total machine running time over the specified working period is proposed. A system considered is comprised of m machines and r

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.775-784
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• 2011

In this paper, we consider the periodic preventive maintenance model for repairable system following the expiration of non-renewing free replacement-repair warranty (NFRRW). 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.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.865-877
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• 2010

This paper considers the periodic preventive maintenance model for a repairable system following warranty expiration. We consider three types of warranty policies: free repair warranty, pro-rata repair warranty, and combination repair warranty. Under these preventive maintenance models, we derive the expressions for the expected cycle length, the total expected cost, and the expected cost rate per unit time. In addition, we explain 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 a Weibull distribution case.

• Journal of Korean Society for Quality Management
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• v.35 no.4
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• pp.140-146
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• 2007

In this paper, we consider a periodic imperfect preventive maintenance(PM) policy in which the system's failure rate after each PM remains unchanged. The system undergoes only minimal repairs at failures between PMs. Exact mathematical formula of the expected cost rate per unit time is derived. Optimal number of PMs and optimal maintenance period are derived by minimizing the expected cost rate per unit time. A numerical example is provided to illustrate the proposed approach under Weibull lifetime distribution.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.86-95
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• 1997

This paper considers a repairable system, which is maintained preventively at periodic times and is minimally repaired at each failure. Most preventive maintenance policies for such repairable systems assume that the cost of minimal repair is constant regardless of its age at failure. However, it is more practical to consider the situations where the cost of minimal repair is dependent not only on its age at failue, but also on the number of preventive maintenance carried out prior to its failure. We consider the preventive maintenance carried out prior to its failure. We consider the preventive maintenance policy with age-dependent minimal repair cost. The optimal policies which minimize the expected cost rate over an infinite time span are discussed. We obtain the optimal period and number of preventive maintenance prior to replacement of the system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.24-31
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• 2018

As a system complexity increases and technology innovation progresses rapidly, leasing the equipment is considered as an important issue in many engineering areas. In practice, many engineering fields lease the equipment because it is an economical way to lease the equipment rather than to own the equipment. In addition, as the maintenance actions for the equipment are costly and need a specialist, the lessor is responsible for the maintenance actions in most leased contract. Hence, the lessor should establish the optimal maintenance strategy to minimize the maintenance cost. This paper proposes two periodic preventive maintenance policies for the leased equipment. The preventive maintenance action of policy 1 is performed with a periodic interval, in which their intervals are the same until the end of lease period. The other policy is to determine the periodic preventive maintenance interval minimizing total maintenance cost during the lease period. In addition, this paper presents two decision-making models to determine the preventive maintenance strategy for leased equipment based on the lessor's preference between the maintenance cost and the reliability at the end of lease period. The structural properties of the proposed decision-making model are investigated and algorithms to search the optimal maintenance policy that are satisfied by the lessor are provided. A numerical example is provided to illustrate the proposed model. The results show that a maintenance policy minimizing the maintenance cost is selected as a reasonable decision as the lease term becomes shorter. Moreover, the frequent preventive maintenance actions are performed when the minimal repair cost is higher than the preventive maintenance cost, resulting in higher maintenance cost.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.18-30
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• 2022

Predicting remaining useful life (RUL) becomes significant to implement prognostics and health management of industrial systems. The relevant studies have contributed to creating RUL prediction models and validating their acceptable performance; however, they are confined to drive reasonable preventive maintenance strategies derived from and connected with such predictive models. This paper proposes a data-driven preventive maintenance method that predicts RUL of industrial systems and determines the optimal replacement time intervals to lead to cost minimization in preventive maintenance. The proposed method comprises: (1) generating RUL prediction models through learning historical process data by using machine learning techniques including random forest and extreme gradient boosting, and (2) applying the system failure time derived from the RUL prediction models to the Weibull distribution-based minimum-repair block replacement model for finding the cost-optimal block replacement time. The paper includes a case study to demonstrate the feasibility of the proposed method using an open dataset, wherein sensor data are generated and recorded from turbofan engine systems.

• Journal of Korean Society for Quality Management
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• v.15 no.1
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• pp.76-81
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• 1987

Past treatment of the single machine maintenance problem has shown that preventive maintenance may be desirable for equipment for which failures are caused at least partially by wear-out factors. In all previous treatment, however, the size of the maintenance-repair crew has been held constant and the optimal maintenance period has then been determined. This paper suggests a simultaneous solution for the maintenance-repair crew size and the optimal maintenance period. The optimal maintenance period is seen to shift as the size of the maintenance-repair crew varies.