• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.85-89
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• 1997

In this paper, we consider a random replacement model with minimal repair, which is a generalization of the random replacement model introduced Lee and Lee(1994). It is assumed that a system is minimally repaired when it fails and replaced only when the accumulated operating time of the system exceeds a threshold time by a supervisor who arrives at the system for inspection according to Poisson process. Assigning the corresponding cost to the system, we obtain the expected long-run average cost per unit time and find the optimum values of the threshold time and the supervisor's inspection rate which minimize the average cost.

• 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 Korean Society for Quality Management
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• v.18 no.2
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• pp.1-8
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• 1990

Replacement policies based on both the system age and the random repair cost are studied. 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 the system fails before age T, the repair cost is estimated and repair is then undertaken if the estimated cost is less than a predetermined limit L ; otherwise, the system is replaced. After repair, the system is as good as new with probability (1-p) or is as good as old with probability P. The expected cost rate is obtained, its behavior is examined, and way of obtaining optimal T and L is explored.

• Journal of the Korea Safety Management & Science
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• v.6 no.1
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• pp.61-70
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• 2004

In this paper, a group replacement policy based on a failure count is analysed. For a group of identical repairable units, a maintenance policy is performed with two phase considerations: a repair interval phase and a waiting interval phase. Each unit undergoes minimal repair at failure during the repair interval. Beyond the interval, no repair is made until a number of failures. The expected cost rate expressions under the policy is derived. A method to obtain the optimal values of decision variables are explored. Numerical examples are given to demonstrate the results.

• 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 Institute of Industrial Engineers
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• v.31 no.4
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• pp.341-348
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• 2005

This paper is concerned with the question of servicing warranties for repairable items. During the warranty period, each time an item fails the manufacturer has the obligation to restore the item to operational condition either by repairing the item or by replacing it with a new item. In this paper, we consider repair-replacement strategies based on the condition of the failed item. For products with phase-type lifetime distributions where the phases represent the condition of the item, we develop algorithms to determine the expected cost of servicing a warranty and use it in making the repair-replacement decision. Illustrative numerical examples are presented. We also propose a dynamic strategy by taking the expected remaining warranty cost into consideration.

• Journal of Korean Society for Quality Management
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• v.39 no.4
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• pp.480-485
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• 2011

This paper presents a spare ordering policy for preventive replacement with minimal repair. To analyze the ordering policy, the failure process is modeled by a non-homogeneous Poisson process. Introducing the ordering, repair, downtime, replacement costs and salvage value, we derive the expected cost effectiveness as a criterion of optimality when the lifetime and lead times for the regular and expedited orders are generally distributed random variables. It is shown that, under certain conditions, there exists a finite and unique optimum ordering time which maximizes the expected cost effectiveness. A numerical example is also included to explain the proposed model.

• Journal of Applied Reliability
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• v.13 no.4
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• pp.229-239
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• 2013

This paper reports a manner to use a Bayesian approach to derive the optimal replacement policy. In order to produce a system with minimal repair warranty, a replacement model with the extended warranty is considered. Within the warranty period, the failed system is minimally repaired by the manufacturer at no cost to the end-user. The failure time is assumed to follow a Weibull distribution with unknown parameters. The expected cost rate per unit time, from the end-user's viewpoints, is induced by the Bayesian approach, and the optimal replacement policy to minimize the cost rate is proposed. Finally, a numerical example illustrating to derive the optimal replacement policy based on the Bayesian approach is described.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.743-752
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• 2006

This paper considers a Bayesian approach to replacement policy model with minimal repair. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. Especially, the overall value function suggested by Jiagn and Ji(2002) is applied to obtain the optimal replacement period. The numerical examples are presented for illustrative purpose.

• Journal of Applied Reliability
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• v.13 no.2
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• pp.77-86
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• 2013

Recently, an extended warranty of a system following the expiration of the basic warranty is becoming increasingly popular to the user. In this respect, we suggest a replacement model following the expiration of extended warranty with minimal repair warranty from the user's point of view in this paper. 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 suggest the optimal replacement period after extended warranty. Finally, a few numerical examples are given for illustrative purpose.