• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.21-31
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• 2002

This paper considers a Bayesian approach to determine an optimal replacement policy for a repairable system with warranty period. The mathematical formula of the expected cost rate per unit time is obtained for two cases : RFRW(renewing free-replacement warranty) and RPRW(renewing pro-rata warranty). 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 replacement policy. Some numerical examples are presented for illustrative purpose.

• Journal of the military operations research society of Korea
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• v.18 no.1
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• pp.110-127
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• 1992

In the preventive replacement policies of system that the failure can be detected through only periodic inspection, there is a penalty cost associated with the lapsed time between system failure and its detection. The system under study is replaced if the system fails before $n^{th}$ inspection, otherwise, preventive replacement is performed at the $n^{th}$ inspection. The decision variables are the inspection interval and the period of preventive replacement. This study presents the optimal preventive replacement policy that minimizes the long-run expected cost per unit time.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.1
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• pp.170-176
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• 2001

An optimization problem to obtain the optimal replacement interval considering the salvage values is studied. The system is minimally repaired at failure and is replaced by new one at age T(periodic replacement policy with minimal repair of Barlow and Hunter〔2〕). Our model assumes that the time horizon associated with the number of replacements is random The total expected cost considering the salvage values with random time horizon is obtained and the optimal replacement interval minimizing the cost is found by numerical methods. Comparisons between non-considered salvage values and this case are made by a numerical example.

• 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 Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.87-92
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• 1995

This paper proposes age replacement policy in stepdown warranty policy. The replacement policy is considered in case of minimally repairable items. And renewal theory is used in analyzing warranty costs. The expected cost per unit time is presented in stepdown warranty policy, free replacement, prorata and hybrid policy. In this article it is assumed that item is replaced at the age of T but the any failure is minimally repaired before the age T. At this point the expected cost per unit time is shown in customer's view point. And numerical example is explored in weibull time-to-failure distribution.

• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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• pp.169-176
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• 2002

To study of binder and fine aggregate a lot of replacement fly-ash concrete, initial characteristics, standard environment of curing temperature $20^{\circ}C$, hot-weather environment, cold weather environment of curing temperature $5^{\circ}C$. Flash concrete tested slump, air contest, setting and Hardening concrete valuated setting period of form, day of age 3, 7, 28 compression strength in sealing curing. Underwater curing specimen compression strength of age 3. 7, 28day used strength change accordingly fly-ash concrete curing temperature. Purpose of study is consultation materials in field that variety of fly-ash replacement concrete mix proportion comparison and valuation. (1) Setting test result, fly-ash ratio of replacement higher delay totting time. Same volume of fly-ash ratio of replacement is lower fly-ash ratio of replacement fine aggregate delay setting time. Setting test in curing temperature $35^{\circ}C$ over twice fast setting in curing temperature $20^{\circ}C$ and all specimen setting delay in curing temperature $5^{\circ}C$. F40 specimen end of setting about 30 time. (2) Experiment result age 28day compression strength more fisher plan concrete then standard environment in curing temperature $20^{\circ}C$, cold weather environment in curing temperature $5^{\circ}C$, most strength F43 is hot-weather environment in curing temperature $35^{\circ}C$ replacement binder 25%, fine aggregate 15%. (3) Hot-weather environment replacement a mount of fly-ash is a same of plan concrete setting period of form. Age 28day compression strength replacement a mount of fly-ash more hot-weather concrete then plan concrete.

• Journal of the military operations research society of Korea
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• v.15 no.1
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• pp.54-62
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• 1989

This paper presents a corrective maintenance model to determine either type of maintenance actions upon failure of the system. Types of maintenance actions considered are minimal repair and replacement. Minimal repair cost is assumed to be random, whereas replacement cost is fixed. A policy, B(t), which determines the type of maintenance action based on the estimated minimal repair cost when the system fails at time t is adopted. To obtain an optimal policy, an expected maintenance cost per unit time is derived and is minimized with respect to B(t).

• Journal of Applied Reliability
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• v.17 no.4
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• pp.316-324
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• 2017

Purpose: The purpose of this study is to determine the replacement cycle applied age replacement policy by reliability analysis based on railway vehicle contactor's failure history data. Method: We performed reliability analysis based on railway vehicle contactor's failure history data. We found a suitable distribution by goodness of fit test and predicted the reliability through estimation of scale & shape parameter. Considering cost information we determined the replacement cycle that minimize the opportunity cost. Result: Suitable distribution was the Weibull and scale parameter & shape parameter are estimated by reliability analysis. The replacement cycle was predicted and MTTF, $B_6$ percentile life were suggested additionally. Conclusion: We confirmed that failure rate type of railway vehicle contactor is degradation model having a time dependent characteristic and examined the replacement cycle in our country's operating environment. We expect that this study result contribute to railway operation agency for maintenance policy decision.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1302-1306
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• 2005

This study has Performed to develop rehabilitation model for determination of optimal rehabilitation time on the Cast Iron Pipes (CIP) with diameter less than 300 mm in water pipeline network and to analysis the sensitivity on the rehabilitation times of developed model. In the result from the application of the field, the renovation time was faster about 10 years than the replacement time. Especially, as the difference between rehabilitation and replacement time on E-CIP was about from 3 to 5 years, and it was thought that the replacement was effective on E-CIP. To sensitivity analysis, the discount rate of coefficient was fixed at 0.08, and the values of initial year break rate(N($t_o$) and growth rate coefficient(A) were adjusted in values of 0.0009, 0.0018, 0.0027, and 0.05, 0.10, 0.15 respectively. When the values of N($t_o$) and A was increased, the results from the time of rehabilitation and replacement was faster It was thought that N($t_o$), 0.018 was reliable values on the applied pipeline through the result of the study. In case of A, the values of A above 0.1 was thought to be Proper.