• 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 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.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 Integrative Natural Science
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• v.14 no.4
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• pp.197-204
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• 2021

Under the two-phase warranty, the warranty period is divided into two intervals, one of which is for renewing replacement warranty, and the other is for minimal repair warranty. Jung^[13] discusses the two types of extended two-phase warranty models. In this paper, we suggest the replacement model after the extended two-phase warranty that has been proposed by Jung^[13]. To determine the optimal replacement policy, we adopt the expected cost rate per unit time. So, the expressions for the total expected cost, the expected length of the cycle and the expected cost rate per unit time from the user's point of view are derived. Also, we discuss the optimal replacement policy and the uniqueness of the solution for the optimization. Furthermore, the numerical examples are provided to illustrate the proposed the replacement model.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.889-901
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• 2003

In this paper, we consider the optimal replacement policies following the expiration of the combination warranty. The combination warranty can be divided into the renewing combination warranty and the non-renewing combination warranty. The criterion used to determine the optimal replacement period is the overall value function based on the expected cost and the expected downtime. Thus, we obtain the expected cost rate per unit time and the expected downtime per unit time for our model. And then 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 Korean Society on Water Environment
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• v.23 no.3
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• pp.356-366
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• 2007

In this paper a methodology is developed to prioritize replacement of water distribution pipes according to the economical efficiency of replacement and assess the long-term effects of water main replacement policies on water distribution systems. The methodology is implemented with MATLAB to develop a computer algorithm which is used to apply the methodology to a case study water distribution system. A pipe break prediction model is used to estimate future costs of pipe repair and replacement, and the economically optimal replacement time of a pipe is estimated by obtaining the time at which the present worth of the total costs of repair and replacement is minimum. The equation for estimating the present worth of the total cost is modified to reflect the fact that a pipe can be replaced in between of failure events. The results of the analyses show that about 9.5% of the pipes in the case study system is required to be replaced within the planning horizon. Analyses of the yearly pipe replacement requirements for the case study system are provided along with the compositions of the replacement. The effects of water main replacement policies, for which yearly replacement length scenario and yearly replacement budget scenario are used, during a planning horizon are simulated in terms of the predicted number of pipe failures and the saved repair costs.

• 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 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.

• 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 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.