• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.139-153
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• 2006

This paper deals with two forms of preventive replacement policy with minimal repair at failure. Those are, 1. the replacement policy I based on the cumulative operating time. 2. the replacement policy II based on the number of failures. The basic assumptions are; (1) the cost of minimal repair at failure is increasing with the number of failures since the last replacement, (2) the equipment fails stochastically with time.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.41-45
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• 2013

Age replacement policy is a commonly policy in maintenance management of spare part. It means that a spare part is always replaced at failure or fixed time after its installation, whichever occurs first. An optimal age replacement policy of spare parts concerns with finding the optimal replacement time determined by minimizing the expected cost per unit time. The age of the part was generally assumed to be a random variable in the past literatures, but in many situations, there are few or even no observed data to estimate the probability distribution of part's lifetime. In order to solve this phenomenon, a new uncertain age replacement policy has been proposed recently, in which the age of the part was assumed to be an uncertain variable. This paper discusses the optimal age replacement policies by dealing with the parts' lifetimes as different distributed uncertain variables. Several results on the optimal age replacement time are provided when the lifetimes are described by the uncertain linear, zigzag and lognormal distributions.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.507-517
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• 1995

The failure rate of an item depends on operational environment. When an item has a chance failure period and a wearout failure period in sequel, the severity of operational environment causes the increase in the slop of wearout failure rate or the increase in the magnitude of chance failure rate. For such a change of operational environment, this paper concerns the change of optimal preventive replacement time. Two preventive replacement policies, age replacement policy and periodic replacement policy with minimal repair, are considered. Investigated properties are: (a) in age replacement policy, optimal preventive replacement time increases as the chance failure rate increases and optimal preventive replacement time decreases as the slope of wearout failure rate increases, and (b) in periodic replacement policy with minimal repair, optimal preventive replacement time increases as the slope of wearout failure rate increases; however, the change of chance failure rate does not alter the optimal preventive replacement time.

• International Journal of Contents
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• v.3 no.1
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• pp.14-18
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• 2007

General replacement policy includes document-based LRU or LFU technique and other various replacement policies are used to replace the documents within cache effectively. But, these replacement policies function only with regard to the time and frequency of document request, not considering the popularity of each web site. In this paper, we present the document replacement policies with regard to the popularity of each web site, which are suitable for modern network environments to enhance the hit-ratio and efficiently manage the contents of cache by effectively replacing documents on intermittent requests by new ones.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.511-516
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• 2006

The data grid computing provides geographically distributed storage resources to solve computational problems with large-scale data. Unlike cache replacement policies in virtual memory or web-caching replacement, an optimal file replacement policy for data grids is the one of the important problems by the fact that file size is very large. The traditional file replacement policies such as LRU(Least Recently Used) LCB-K(Least Cost Beneficial based on K), EBR(Economic-based cache replacement), LVCT(Least Value-based on Caching Time) have the problem that they have to predict requests or need additional resources to file replacement. To solve theses problems, this paper propose SBR-k(Sized-based replacement-k) that replaces files based on file size. The results of the simulation show that the proposed policy performs better than traditional policies.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.144-157
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• 1999

In this paper, we consider a new preventive replacement policy for the system which deteriorates while it is in operation with an increasing failure rate. The system is subject to two types of failure. A type 1 failure is repairable while a type 2 failure is not repairable. In the new policy, a system is replaced at the age of $t_p$ or at the instant the$\textsc{k}^{th}$ type 1 failure occurs, whichever comes first. However, if a type 2 failure occurs before a preventive replacement is performed, a failure replacement should be made. We assume that a type 1 failure can be rectified with a minimal repair. We also assume that a replacement takes a non-negligible amount of time while a minimal repair takes a negligible amount of time. Under a cost structure which includes a preventive replacement cost, a failure replacement cost and a minimal repair cost, we develop a model to find the optimal ($\textsc{k},t_p$) policy which minimizes the expected cost per unit time in the long run while satisfying a system availability constraint.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.52-58
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• 2013

Replacement policy is one of the key factors determining the effectiveness of a cache. The LRU replacement policy has remained the standard for caches for many years. However, the traditional LRU has ineffective performance in zero-reuse line intensive workloads, although it performs well in high temporal locality workloads. To address this problem, We propose a new replacement policy; DCR(Dynamic Counter based Replacement) policy. A temporal locality of workload dynamically changes across time and DCR policy is based on the detection of these changing. DCR policy improves cache miss rate over a traditional LRU policy, by as much as 2.7% at maximum and 0.47% at average.

• 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.

• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.117-122
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• 2011

In this paper, we suggest the optimal replacement policy following the expiration of repair warranty when the cost of minimal repair depends on the age of system. To do so, we first explain the replacement model under repair warranty. And then the optimal replacement policy following the expiration of repair warranty is discussed from the user's point of view. The criterion used to determine the optimality of the replacement model is the expected cost rate per unit time, which is obtained from the expected cycle length and the expected total cost for our replacement model. The numerical examples are given for illustrative purpose.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.403-412
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• 1999

A block replacement policy where at failure the item is either replaced by a new or used item or remains inactive until the next planned replacement is considered. in this paper our interests are focused on reusing all the used items created by the policy. Numerical results for the case where the underlying life distribution is gamma are obtained.