• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.7
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• pp.34-40
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• 2014

In this paper, we want to know the optimal replacement cycle(time) for this study was performed. The optimal preventive replacement age can be fond by finding the value of time that minimizes the cost function(model of Barlow and Jardine). In addition, The reliability of the relay according to the service environment were studied. The use of the exchange relay period is longer, and maintenance cost rate(per hour) may increase, and also the reliability may cause a decline. In addition, considering the preventive maintenance and purchase order, a representative relay(RAX-L440-A type) life was calculated.

• 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 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.

• Journal of Korean Society for Quality Management
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• v.13 no.1
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• pp.51-55
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• 1985

A replacement policy for a system subject to shocks where each shock increases the running cost is considered. The shocks arrive to the system according to a nonhomogeneous Poisson process. Optimal replacement policy to minimize the long-run expected cost rate is obtained and some numerical examples are given.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.59-63
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• 1987

An age replacement policy is considered for a system under a stepdown warranty. It is assumed that only minimal repairs are performed for failures occurred before age T.A unique optimal value of T which minimiges the expected cost rate is obtained. The cases of the free replacement warranty, prorata warranty and hybrid warranty are also considered and some numerical examples are given.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.185-192
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• 2003

In this paper, the properties on the optimal replacement policies for the general failure model are developed. In the general failure model, two types of system failures may occur : one is Type I failure (minor failure) which can be removed by a minimal repair and the other, Type II failure (catastrophic failure) which can be removed only by complete repair. It is assumed that, when the unit fails, Type I failure occurs with probability 1-p and Type II failure occurs with probability p, $0\leqp\leq1$. Under the model, the system is minimally repaired for each Type I failure, and it is repaired completely at the time of the Type II failure or at its age T, whichever occurs first. We further assume that the repair times are non-negligible. It is assumed that the minimal repair times in a renewal cycle consist of a strictly increasing geometric process. Under this model, we study the properties on the optimal replacement policy minimizing the long-run average cost per unit time.

• 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.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 the Korean Data and Information Science Society
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• v.21 no.5
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• pp.873-882
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• 2010

This paper considers a Bayesian approach to replacement policy following the expiration of non-renewing combination warranty. The non-renewing combination warranty is the combination of the non-renewing free replacement warranty and the non-renewing pro-rata replacement warranty. 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 times are assumed to follow a Weibull distribution with uncertain parameters, we propose the optimal replacement policy based on the Bayesian approach. The overall value function suggested by Jiang and Ji (2002) is utilized to determine the optimal replacement period. Also, the numerical examples are presented for illustrative purpose.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.393-403
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• 2003

In this paper, various replacement policies for the general failure model are considered. There are two types of failure in the general failure model. One is Type I failure (minor failure) which can be removed by a minimal repair and the other is Type II failure (catastrophic failure) which can be removed only by a complete repair. In this model, when the unit fails at its age t, Type I failure occurs with probability 1-p(t) and Type II failure occurs with probability p(t), $0{\leq}p(t){\leq}1$. Under the model, optimal replacement policies for the long-run average cost rate and the limiting efficiency are considered. Also taking the cost and the efficiency into consideration at the same time, the properties of the optimal policies under the Cost-Priority-Criterion and the Efficiency-Priority-Criterion are obtained.