• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.263-271
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• 1997

This paper presents a preventive maintenance model for determining the preventive replacement period of a system in which a failure rate is affected by the cumulative damage of fault and inspection. Especially, the failure rate function is considered to be a function of the cumulative damage of the fault and inspection time. Types of replacement considered are preventive replacement and failure replacement. Failure rate and expected cost function between replacement are derived. An optimal policy is obtained that minimizes the average cost per unit time for preventive replacement, failure replacement, inspection and repair.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.651-662
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• 1996

This paper concerns with preventive replacement under periodic inspections for an item (system) which is in a state of preparedness. The item is subject to wear. The item fails randomly but the failure rate depends on the accumulated wear. The item is preventively replaced if it survives a certain wear limit at periodic inspections. The foiled item is, however, replaced at periodic inspections. Given the costs for replacements and inspections, and the penalty cost of the time elapsed between failure und its detection, the optimal wear limit according to the long-run expected cost per unit time criterion is derived. It has been proved that the optimal wear limit is unique if an item has increasing weer-dependent failure rate. A numerical example for a stationary gamma wear process with Weibull distributed failure is given to show its applicability.

• Journal of Applied Reliability
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• v.14 no.2
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• pp.122-128
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• 2014

In this paper, we consider the periodic preventive maintenance model for a repairable system following the expiration of extended warranty under replacement-repair warranty. Under the replacement-repair warranty, the failed system is replaced or minimally repaired by the manufacturer at no cost to the user. Also, under extended warranty, the failed system is minimally repaired by the manufacturer at no cost to the user during the original extended warranty period. As a criterion of the optimality, we utilize the expected cost rate per unit time during the life cycle from the user's perspective. And then 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 Korean Institute of Industrial Engineers
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• v.11 no.1
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• pp.3-10
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• 1985

Periodic replacement policies are proposed for a system whose repair cost, when it fails, can be estimated by inspection. The system is replaced when it reaches age T (Policy A), or when it fails for the first time after age T (Policy B). If it fails before reaching age T, the repair cost is estimated and minimal repair is then undertaken if the estimated cost is less than a predetermined limit L; otherwise, the system is replaced. The expected cost rate functions are obtained, their behaviors are examined, and ways of obtaining optimal T and L are explored.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.201-214
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• 2020

Purpose: The purpose of this paper is to determine an optimal number of cycle times for the replacement under the circumstance where the system is replaced at the periodic time and the multiple number of working cycles whichever occurs first and the system is minimally repaired between the replacements if it fails. Methods: The system is replaced at periodic time () or cycle time, whichever occurs first, and is repaired minimally when it fails between successive replacements. To determine the optimal number of cycle times, the expected total cost rate is optimized with respect to the number of cycle times, where the expected total cost rate is defined as the ratio of the expected total cost between replacements to the expected time between replacements. Results: In this paper, we conduct a sensitivity analysis to find the following results. First, when the expected number of failures per unit time increases, the optimal number of cycle times decreases. Second, when the periodic time for replacement becomes longer, the optimal number of cycle times decreases. Third, when the expected value for exponential distribution of the cycle time increases, the optimal number of cycle times increases. Conclusion: A mathematical model is suggested to find the optimal number of cycle times and numerical examples are provided through the sensitivity analysis on the model parameters to see the patterns for changes of the optimal number of cycle times.

• Journal of Korean Society for Quality Management
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• v.20 no.2
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• pp.33-43
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• 1992

Items are assumed to fail by degradation. An appropriate stochastic model of such item is a cumulative process in which an item can fail only when the total amount of wear exceeds a prespecified failure level. This paper presents replacement policy in which an item is replaced at a certain level of wear before failure or at failure, whichever occurs first. Yet, when measuring the item wear level is very expensive, destructive or time-consuming, it may be economical to use substitutive characteristics that are correlated with the item wear level and relatively inexpensive to measure. The item's wear level could usually be estimated by monitoring such substitutive characteristics only except for a breakdown, which may be observed immediately at its occurrence. The purpose of this paper is to find an optimal periodic replacement policy based on such substitutive characteristics that balance the cost of replacement with the cost of failure and result in a minimum total long-run average cost per unit time. The optimal level of substitutive characteristics to replace the item is obtained. Numerical example illustrate how the model can be used to determine the optimal replacement policy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.139-146
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• 1995

This study is concerned with cost analysis in periodic maintenance policy. Generally periodic maintenance policy in which item is repaired periodic interval times. And in the article minimal repair is considered. Minimal repair means that if a unit fails, unit is instantaneously restored to same hazard rate curve as before failure. In the paper periodic maintenance policy with minimal repair is as follows; Operating unit is periodically replaced in periodic maintenance time, if a failure occurs between minimal repair and periodic maintenance time, unit is replaced by a spate until the periodic time comes. Also unit undergoes minimal repair at failures in minimal-repair-for-failure interval. Then total expected cost per unit time is calculated according to maintenance period and scale parameter of failure distribution. Total cost factors ate included operating, fixed, minimal repair, periodic maintenance and replacement cost Numerical example is shown in which failure time of system has erlang distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.287-295
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• 1995

This paper is concerned with cost analysis model in periodic maintenance policy. Generally periodic maintenance policy in which item is repaired periodic interval times. And in the article minimal repair is considered. Mimimal repair means that if a unit fails, unit is instantaneously restored to same hazard rate curve as before failure. In the paper periodic maintenance policy with minimal repair is as follows; Operating unit is periodically replaced in periodic maintenance time, if a failure occurs between minimal repair and periodic maintenance time, unit is replaced by a new item until tile periodic maintenance time comes. Also unit undergoes minimal repair at failures in minimal-repair-for-failure interval. Then total expected cost per unit time is calculated according to scale parameter of failure distribution. Maintenance cost factors are included operating, fixed, minimal repair, periodic maintenance and new item replacement cost. Numerical example is shown in which failure time of system has weibull distribution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.193-196
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• 1997

In this paper we consider a Bayesian theoretic approach to periodic incomplete preventive maintenance with minimal repair at failure. We assume that the system failure rate is increasing as the frequency of PM increases and that the system is replaced at the K-th PM under this maintenance strategy. The optimal policies which minimize the expected cost rates are discussed. We seek the optimal periodic PM interval x and replacement time K under a Weibull failure intensity. Assuming suitable prior distribution for the Weibull parameters, we derive the posterior distribution incorporating failure data and obtain the updated optimal replacement strategies.

• Journal of Korean Institute of Industrial Engineers
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• v.4 no.1
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• pp.1-3
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• 1978

This paper presents a model for determining the optimal number of minimal repairs before replacement. The basic concept parallels the periodic replacement model with minimal repair at failure introduced by Barlow and Hunter, only difference being the replacement signalled by the number of previous minimal repairs performed on the unit. In the case of Weibull distribution, which is widely used as a general failure distribution, the optimal solution could be obtained numerically and seems more cost effective compared to the Barlow and Hunter's Policy II.