• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.139-146
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• 1995

This study is concerned with cost analysis in periodic maintenance policy. Generally periodic maintenance policy in which item is repaired periodic interval times. And in the article minimal repair is considered. Minimal repair means that if a unit fails, unit is instantaneously restored to same hazard rate curve as before failure. In the paper periodic maintenance policy with minimal repair is as follows; Operating unit is periodically replaced in periodic maintenance time, if a failure occurs between minimal repair and periodic maintenance time, unit is replaced by a spate until the periodic time comes. Also unit undergoes minimal repair at failures in minimal-repair-for-failure interval. Then total expected cost per unit time is calculated according to maintenance period and scale parameter of failure distribution. Total cost factors ate included operating, fixed, minimal repair, periodic maintenance and replacement cost Numerical example is shown in which failure time of system has erlang distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.263-271
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• 1997

This paper presents a preventive maintenance model for determining the preventive replacement period of a system in which a failure rate is affected by the cumulative damage of fault and inspection. Especially, the failure rate function is considered to be a function of the cumulative damage of the fault and inspection time. Types of replacement considered are preventive replacement and failure replacement. Failure rate and expected cost function between replacement are derived. An optimal policy is obtained that minimizes the average cost per unit time for preventive replacement, failure replacement, inspection and repair.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.73-78
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• 2005

This paper considers a preventive maintenance policy following the expiration of renewing warranty, Most preventive maintenance models assume that each PM costs a fixed predetermined amount regardless of the effectiveness of each PM. However, it seems more reasonable to assume that the PM cost depends on the degree of effectiveness of the PM activity. In this paper we consider a periodic preventive maintenance policy following the expiration of renewing warranty when the PM cost is an increasing function of the PM effect. The optimal number and period for the periodic PM policy with effect dependent cost that minimize the expected cost rate per unit time over an infinite time span are obtained.

• 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.

• 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.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.909-923
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• 2008

This paper considers the replacement model and the preventive maintenance model following the expiration of combination warranty for a repairable system. If the system fails after the combination warranty is expired, then it is minimally repaired at each failure. The criterion used to determine the optimal replacement policy and the optimal preventive maintenance policy is the overall value function based on the expected cost rate per unit time and the expected downtime per unit time. The numerical examples are presented for illustrative purpose when the failure time follows a Weibull distribution.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.85-89
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• 1997

In this paper, we consider a random replacement model with minimal repair, which is a generalization of the random replacement model introduced Lee and Lee(1994). It is assumed that a system is minimally repaired when it fails and replaced only when the accumulated operating time of the system exceeds a threshold time by a supervisor who arrives at the system for inspection according to Poisson process. Assigning the corresponding cost to the system, we obtain the expected long-run average cost per unit time and find the optimum values of the threshold time and the supervisor's inspection rate which minimize the average cost.

• 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 Society of Automotive Engineers
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• v.14 no.6
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• pp.113-126
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• 1992

Recently the multi-kind, small-amount manufacturing system has been replacing the mass manufacturing system, and domestic machining inustry also is eager to absorb the new technology because of its high productivity and cost reduction. The optimization of the cutting condition has been a vital problem in the machining industry, which would help increase the productivity and raise the international competitiveness. It is intended in this study to investigate the machining costs per unit time which is essential to the analysis of the optimal cutting condition, to computer the cutting speed that lead to the minimum machining costs and the maximum production to suggest the cutting speed range that enables efficient speed cutting, and to review the machining economy in relation to cutting depth and feed. Also considered are the optimal cutting speed and prodution rated in rrelation with feed. It is found that the minimum-cost cutting speed increases and the efficient cutting speed range is reduced as machining cost per unit time increases since the cutting speed for maximum production remains almost constant. The machining cost is also lowered and the production rate increases as the feed increases, and the feed should be selected to satisfy the required surface roughness. The machining cost and production rate are hardly affected by the cutting depth if the cutting speed stays below 100m/min, however, they are subject to change at larger cutting depth and the high-efficient speed range also is restricted. It can be established an adaptive optimal cutting conditions can be established in workshop by the auto-selection progam for optimal operation. It is expected that this method for choosing the optimal cutting conditions might contribute to the improvement of the productivity and reduced the cost. It is highly recommended to prepare the optimal cutting conditionthus obtained for future use in the programing of G-function of CNC machines. If proper programs that automatically select the optimal cutting conditions should be developed, it would be helpful to the works being done in the machine shops and would result in noticeable production raise and cost reduction.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.144-157
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• 1999

In this paper, we consider a new preventive replacement policy for the system which deteriorates while it is in operation with an increasing failure rate. The system is subject to two types of failure. A type 1 failure is repairable while a type 2 failure is not repairable. In the new policy, a system is replaced at the age of $t_p$ or at the instant the$\textsc{k}^{th}$ type 1 failure occurs, whichever comes first. However, if a type 2 failure occurs before a preventive replacement is performed, a failure replacement should be made. We assume that a type 1 failure can be rectified with a minimal repair. We also assume that a replacement takes a non-negligible amount of time while a minimal repair takes a negligible amount of time. Under a cost structure which includes a preventive replacement cost, a failure replacement cost and a minimal repair cost, we develop a model to find the optimal ($\textsc{k},t_p$) policy which minimizes the expected cost per unit time in the long run while satisfying a system availability constraint.