• International Journal of Reliability and Applications
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• v.12 no.2
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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.

• International Journal of Reliability and Applications
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• v.10 no.1
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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.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.61-83
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• 1991

There has been a great deal of research dealing with the optimal replacement of stochastically deteriorating equipment and research in queueing systems with a finite calling population. However. there has been a lack of research which combines these two areas to deal with optimal replacement for a fixed number of machines and a limited number of repairmen. In this research, an optimal control policy for replacement involving two machines and one repairman is developed by investigating a class of age replacement policies in the context of controlling a G/M/1 queueing system with a finite calling population. The control policy to be imposed on this problem is an age-dependent control policy, described by the control limit $t^{\ast}$. The control limit is operational only when the repairman is idle; that is. if both machines are working, as soon as a machine reaches the age $t^{\ast}$ it is taken out of service for replacememt. We obtain the ${\epsilon}$-optimal control age which will minimize the long-run average system cost. An algorithm is developed that is applicable to general failure time distributions and cost functions. The algorithm does not require the condition of unimodality for implementation.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.233-238
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• 2013

This article concerns a profit model in a repair limit replacement problem with imperfect repair. If a system fails, we should decide whether we repair the failed system (repair option) or replace it by new one (replacement option with a lead time). We assume that repair times are random variables and can be estimated before repair with estimation error. If the estimated repair time is less than the specified limit (repair time limit), the failed unit is repaired but the unit after repair is different from the new one (imperfect repair). Otherwise, we order a new unit to replace the failed unit. The long run average profit (expected profit rate) is used as an optimization criterion and the optimal repair time limit maximizes the expected profit rate. Some special cases are derived.

• 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 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 the Korea Institute of Building Construction
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• v.5 no.2 s.16
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• pp.153-159
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• 2005

This study is to choose the optimal mixture and to analyze the sensibility properties of High strength concrete and mass concrete to apply the high rising building. The main experimental variables were water/binder ratio $39\%,\;33\%,\;35\%\;and\;37\%$, replacement ratio of fly ash $5\%,\;10\%\;and\;15\%$, in the high strength concrete and water/binder ratio $39\%,\;41\%\;and\;43\%$, replacement ratio of fly ash $10\%,\;20\%\;and\;30\%$, in the man concrete. According to the test results, the principal conclusions are summarized as follows. 1) The slump(or slump flow) and air content of fresh concrete were found to be the highest in the elapsed time 30 minutes. 2) The optimal mixture conditions are W/B $40\%$, FA $25\%$ in the mass concrete and W/B $33.4\%$, FA $15\%$ in the high strength concrete. 3) The ranges of sensibility are satisfied in the moisture content ${\pm}l\%\;and\;S/a\;{\pm}2\%$.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.775-784
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• 2011

In this paper, we consider the periodic preventive maintenance model for repairable system following the expiration of non-renewing free replacement-repair warranty (NFRRW). Under this preventive maintenance model, we derive the expressions for the expected cycle length, the expected total cost and the expected cost rate per unit time. Also, 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.17 no.30
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• pp.51-57
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• 1994

This paper considers the problem of equipment replacement A equipment replacement problem is treated in a thchnological development environment. Our model assumes that the costs associated with the presently available thchnology and future technology is known, but the appearance times of future technology is uncertain. A cost model is presented, and method is suggested for finding the optimal operating time for replacement A numerical example is shown.

• Journal of the military operations research society of Korea
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• v.10 no.2
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• pp.61-73
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• 1984

A block replacement policy using items with different reliability is discussed. We divide system unit failure modes into two modes and use less reliable unit when operating unit fails near the planned preventive replacement time. In this policy, item A has two failure modes. Mode-1 failure is removed by minimal repair, mode-2 failure by replacement. If mode-2 failure of item A happens in (0, $T-{\delta}$), failure item A is replaced by new item A. If mode-2 failure of item A happens in ($T-{\delta}$, T), failure item A is replaced by new item B. Item B should be cheaper and less durable than item A. Under this policy, we determine the preventive replacement interval $T^{*}$ and the interval ${\delta}^{*}$ of item B replacement which minimize the cost rate per unit time.