• Industrial Engineering and Management Systems
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• 제12권1호
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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.

• International Journal of Reliability and Applications
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• 제10권1호
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• pp.33-42
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• 2009

In most of literatures of age replacement policy, the authors consider the case that a new item starts operating at time zero and is to be replaced by new one at time T. It is, however, often to purchase used items because of the limited budget. In this paper, we consider age replacement policy of a used item whose age is $t_0$. The mathematical formulas of the expected cost rate per unit time are derived for both infinite-horizon case and finite-horizon case. For each case, we show that the optimal replacement age exists and is finite and investigate the effect of the age of the used item.

• International Journal of Reliability and Applications
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• 제12권2호
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• pp.131-143
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• 2011

In most of literatures of age replacement policy, the authors consider the case that a new item starts operating at time zero and is to be replaced by new one at time T. It is, however, often to purchase used items because of the limited budget. In this paper, we consider age replacement policy of a used item whose age is $t_0$. The mathematical formulas of the expected cost rate per unit time are derived for both infinite-horizon case and finite-horizon case. For each case, we show that the optimal replacement age exists and is finite and investigate the effect of the age of the used item.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.280-286
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• 2016

Purpose: Recently, Jiang defines the tradeoff B life to minimize a sum of life lost by preventive maintenance (PM) and corrective maintenance (CM) contribution parts and sets up an optimal replacement age of age replacement policy as this tradeoff life. In this paper, Jiang's model only considering the known lifetime distribution is extended by assigning different weights to two parts of PM and CM in order to reflect the practical maintenance situations in application. Methods: The new age replacement model is formulated and the meaning of a weight factor is expressed with the implied cost of failure under asymptotic expected cost model and also discussed with one-cycle expected cost criterion. Results: The proposed model is applied to Weibull and lognormal lifetime distributions and optimum PM replacement ages are derived with corresponding implied cost of failure. Conclusion: The new age replacement policy to escape the estimation of cost of failure in classical asymptotic expected cost criterion based on the renewal process is provided.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권3호
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• pp.188-196
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• 2017

Purpose: The purpose of this research is to determine optimal replacement age using non-informative prior information and Bayesian method. Methods: We propose a novel approach using Bayesian method to determine the optimal replacement age in block replacement policy by defining the prior probability with data on failure time and repair time. The Marcov Chain Monte Carlo simulation is used to investigate the asymptotic distribution of posterior parameters. Results: An optimal replacement age of block replacement policy is determined which minimizes cost and nonoperating time when no information on prior distribution of parameters is given. Conclusion: We find the posterior distribution of parameters when lack of information on prior distribution, so that the optimal replacement age which minimizes the total cost and maximizes the total values is determined.

• 대한산업공학회지
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• 제21권4호
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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 Reliability and Applications
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• 제12권2호
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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.

• International Journal of Reliability and Applications
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• 제1권1호
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• pp.27-38
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• 2000

In a recent paper Iskandar ＆ Sandoh (1999) studied an opportunity-based age replacement policy for a system which has a warranty period (0,S]. When the system fails at age x $\leq$ S a minimal repair is performed. If an opportunity occurs to the system at age x, S $\leq$ x $\leq$ T, we take the opportunity with probability p to preventively replace the system, while we conduct a corrective .replacement when its fails in (S,T). Finally, if its age reaches T, we perform a preventive replacement, Under this policy the design variable is T. For the case when opportunities occur according to a homogeneous Poisson process, the long-run average cost of this policy was formulated and studied analytically by Iskandar & Sandoh (1999). The same problem is here analysed by using a graphical technique based on scaled TTT-transforms. This technique gives, among other things, excellent possibilities for different types of sensitivity analysis. We also extend the discussion to the situation when we have to estimate T based on times to failure.

• 산업경영시스템학회지
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• 제18권33호
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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.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권4호
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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.