• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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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.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.147-151
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• 2002

Burn-in is a widely used method to eliminate initial failures. Preventive maintenance policy such as block replacement with minimal repair at failure is often used in field operation. In this paper burn-in and maintenance policy are taken into consideration at the same time. The cost of a minimal repair is assumed to be a non-decreasing function of its age. The problems of determining optimal burn-in times and optimal maintenance policy are considered.

• 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 Information Processing Systems
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• v.19 no.2
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• pp.149-163
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• 2023

Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.

• Korean Management Science Review
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• v.26 no.3
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• pp.145-156
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• 2009

The probability distribution of the repair process should be determined to choose the optimal spare level of a weapon system with a queueing model. Though most weapon systems have a multi-step repair process, previous studies use the exponential distribution for the multi-step repair process. But the PH distribution is more appropriate for this case. We utilize the PH distribution on a queueing model and solve it with MGM(Matrix Geometric Method). We derive the optimal spare level using the PH distribution and show the difference of results between the PH and exponential distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.61-69
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• 2020

Systems such as database and socal network systems have been broadly used, and their unexpected failure, with great losses and sometimes a social confusion, has received attention in recent years. Therefore, it is an important issue to find optimal maintenance plans for such kind of systems from the points of system reliability and maintaining cost. However, it is difficult to maintain a system during its working cycle, since stopping works might incur users some troubles. From the above viewpoint, this paper discusses minimal repair maintenance policy with periodic replacement, while considering the random working cycles. The random working cycle and periodic replacement policies with minimal repair has been discussed in traditional literatures by usually analyzing cases for the nonstopping works. However, maintenance can be more conveniently done at discrete time and even during the working cycle in real applications. So, we propose that periodic replacement is planned at discrete times while considering the random working cycle, and moreover provide a model in which system, with a minimal repair at failures between replacements, is replaced at the minimum of discrete times KT and random cycles Y. The average cost rate model is used to determine the optimal number of periodic replacement.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.53-58
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• 2000

In many cases, it is more practical and economical to repair a system than to replace the whole system or to perform a complete overhaul when it fails. The age replacement policy with minimal repair at failure is considered. The system is replaced every time its age reaches at $T_0$. For each intervening failure only minimal repair is done. The minimal repair times in a renewal period are increasing in the sense that the minimal repair times constitute a strictly increasing geometric process. The long-run expected cost rate Is obtained and the properties of the existence and the uniqueness of the optimal policy minimizing the long-run expected cost rate are derived.

• Journal of Korean Society for Quality Management
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• v.15 no.1
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• pp.13-19
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• 1987

This paper discusses the methods of determining optimal warranty period for repairable goods. The demand of the product is assumed to increase with the length of the warranty period. Good-as-new repair and minimal repair models are considered. The method of obtaining optimal warranty period is explored when the failure distribution is an exponential or a Weibull. The case of discounting all associated costs continuously over time is also considered.

• 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 Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.273-281
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• 2007

The decision of how long performing system burn-in must be answered with a probabilistic model of a system lifetime at which infant mortality failures created during assembly processes are quantified. In this paper, we propose such a model which is modified from previous results. Using the system model, we derived system reliability in terms of component and system burn-in times for the two cases of minimal repair at system failure and of component replacement and connection repair at their failure times. The procedure is illustrated with a bridge system and the optimal system burn-in times are obtained for maximizing system reliability. The result suggests that an assumption of minimal repair at system failure may underestimate the optimal burn-in time in practice.