• 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.30 no.4
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• pp.94-105
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• 2002

In this paper, replacement problems for a deteriorating system are considered. In the system under consideration, the successive lifetimes after repair become shorter and shorter, while the consecutive repair times become longer and longer. More specifically, the lifetimes of the system form a nonhomogeneous Poisson process, whereas the consecutive repair times constitute a stochastically increasing geometric process. Optimal replacement policies for the long-run average cost rate and the steady state availability are considered. Also taking the cost and the availability into consideration at the same time, the properties of optimal policies under the Cost Priority Policy and the Availability Priority Policy are obtained.

• Journal of Applied Reliability
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• v.11 no.4
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• pp.409-417
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• 2011

In this paper, we consider a replacement model following the expiration of warranty. In other words, this paper proposes the optimal replacement policy for a repairable system following the expiration of payable renewing replacement-non-renewing minimal repair warranty. The expected cost rate per unit time from the user's perspective is used to determine the optimality of the replacement policy. Thus, we derive the expressions for the expected cycle length and the expected total cost to obtain the expected cost rate per unit time. Finally, the numerical examples are presented for illustrative purpose.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.78-89
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• 2022

The purpose of this study was to propose useful suggestion by analyzing preventive replacement policy under which there are minor and major failure. Here, major failure is defined as the failure of system which causes the system to stop working, however, the minor failure is defined as the situation in which the system is working but there exists inconvenience for the user to experience the degradation of performance. For this purpose, we formulated an expected cost rate as a function of periodic replacement time and the number of system update cycles. Then, using the probability and differentiation theory, we analyzed the cost rate function to find the optimal points for periodic replacement time and the number of system update cycles. Also, we present a numerical example to show how to apply our model to the real and practical situation in which even under the minor failure, the user of system is not willing to replace or repair the system immediately, instead he/she is willing to defer the repair or replacement until the periodic or preventive replacement time. Optimal preventive replacement timing using two variables, which are periodic replacement time and the number of system update cycles, is provided and the effects of those variables on the cost are analyzed.

• 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 the military operations research society of Korea
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• v.24 no.1
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• pp.98-109
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• 1998

This study develops a maintenance strategy for a reparable 2-unit standby system. The maintenance strategy implies the waiting time to call the repair facility when the unit-1 fails. Almeida and Souza set up the multi-attribute utility function consisting of system availability and repair cost for several maintenance strategies and decide the optimal maintenance strategy that maximize the expected value of the utility function. We decide the optimal maintenance strategy satisfying the following two criteria about the utility function : maximum variance using Almeida and Souza's utility function. It both criteria are not satisfied at the same time for every strategies, the strategy maximizing the lower confidence limit for expected utility function is regarded as an optimal one.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.99-106
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• 1999

This paper considers an imperfect repair model for which the repairable system is maintained preventively at periodic times and is replaced by a new system when a predetermined number of preventive maintenance has been applied. our main objective of this is to determine the optimal number of preventive maintenances before the system is replaced and the optimal length of interval between two consecutive preventive maintenances under a new repair model which is referred to as an ineffective preventive maintenance. Such a model assumes a periodic preventive maintenance in which the system is effectively maintained with a certain probability. Otherwise the system is not improved at all after each maintenance and thus the failure rate remains the same as before. The criteria to determine the optimal number of preventive maintenances and length of period is the expected cost rate per unit time for an infinite time span. We give the explicit expressions for the expected cost rate per unit time. Some numerical examples are presented for illustrative purposes.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.466-475
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• 1999

A backward Dynamic Programming(DP) model for the optimal facility replacement decision problem during a finite planning horizon is presented. Multiple alternative challengers to a current defender are considered. All facilities are assumed to have finite service lives. The objective of the DP model is to maximize the profit over a finite planning horizon. As for the cost elements, purchasing cost, maintenance costs and repair costs as well as salvage value are considered. The time to failure is assumed to follow a weibull distribution and the maximum likelihood estimation of Weibull parameters is used to evaluate the expected cost of repair. To evaluate the revenue, the rate of operation during a specified period is employed. The cash flow component of each challenger can vary independently according to the time of occurrence and the item can be extended easily. The effects of inflation and the time value of money are considered. The algorithm is illustrated with a numerical example. A MATLAB implementation of the model is used to identify the optimal sequence and timing of the replacement.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.56
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• pp.1-8
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• 2000

We present in this paper an optimal stocking policy for a repairable inventory system under reliability improvement. For this purpose we illustrate commercial flight lines with a large number of planes. This model is supported by a central repair facility. For modeling the nonstationary M/M/s system we implemented SIMAN for computing the time dependent number of units in the repair facility with any number of units. In this model we provide the required inventory level at each location. 1y month. for various levels of associated stock-out risk.