• 산업경영시스템학회지
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• 제41권1호
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• pp.110-117
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• 2018

Machines and facilities are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. By the result of degeneration, non-conforming products and malfunction of machine occur. Therefore a periodic preventive resetting the process is necessary. This type of preventive action is called 'preventive maintenance policy.' Preventive maintenance presupposes that the preventive (resetting the process) cost is smaller than the cost of failure caused by the malfunction of machine. The process mean shift problem is a field of preventive maintenance. This field deals the interrelationship between the quality cost and the process resetting cost before machine breaks down. Quality cost is the sum of the non-conforming item cost and quality loss cost. Quality loss cost is due to the deviation between the quality characteristics from the target value. Under the process mean shift, the quality cost is increasing continuously whereas the process resetting cost is constant value. The objective function is total costs per unit wear, the decision variables are the wear limit (resetting period) and the initial process mean. Comparing the previous studies, we set the process variance as an increasing concave function and set the quality loss function as Cpm+ simultaneously. In the Cpm+, loss function has different cost coefficients according to the direction of the quality characteristics from target value. A numerical example is presented.

• 한국압력기기공학회 논문집
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• 제10권1호
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• pp.37-43
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• 2014

Nuclear power plants(NPPs) are consisted of power production functions and safety functions preventing leakage of radiation. Operators working in NPPs shall maintain these functions during an operation period through various activities such as improvement & modification, corrective maintenance, preventive maintenance and surveillance test. According to the performance of these work activities, there are configuration changes in NPPs systems. Its changes cause the increase of safety risks(CDF) and plant trip risks. Recently, the importance of risk management is increasing gradually in the operation process of NPPs. Therefore, this paper presents the work management methods using the various risk monitoring systems during power operation and overhaul period. Also this paper suggests the optimum application ways of risk systems for work management.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권3호
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• pp.246-255
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• 2017

Purpose: This study proposes the optimal PM (preventive maintenance) policy of leased equipment for lessee's decision-making using two types of reliability condition. Methods: We consider reliability threshold based PM model. Equipment reliability is estimated and used as condition variable. The effect of repair for maintenance is imperfect and represented by age reduction factor. Results: We provide two PM policies. Policy 1 is focused on minimized total cost. This policy guarantees reliability threshold until last maintenance action. Policy 2 focus on maintaining reliability threshold during leased period. The proposed approach provides optimal reliability threshold under number of PM. Through result, we finally construct decision-making process for lessee using reliability threshold and end of reliability. Conclusion: This study provides two PM policy for lessee's decision-making. Through numerical example, we get a result of optimal reliability threshold, number of PM, optimum alternative under lessee's reliability condition.

• 산업경영시스템학회지
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• 제42권4호
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• pp.145-152
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• 2019

All machines deteriorate in performance over time. The phenomenon that causes such performance degradation is called deterioration. Due to the deterioration, the process mean of the machine shifts, process variance increases due to the expansion of separate interval, and the failure rate of the machine increases. The maintenance model is a matter of determining the timing of preventive maintenance that minimizes the total cost per wear between the relation to the increasing production cost and the decreasing maintenance cost. The essential requirement of this model is that the preventive maintenance cost is less than the failure maintenance cost. In the process mean shift model, determining the resetting timing due to increasing production costs is the same as the maintenance model. In determining the timing of machine adjustments, there are two differences between the models. First, the process mean shift model excludes failure from the model. This model is limited to the period during the operation of the machine. Second, in the maintenance model, the production cost is set as a general function of the operating time. But in the process mean shift model, the production cost is set as a probability functions associated with the product. In the production system, the maintenance cost of the equipment and the production cost due to the non-confirming items and the quality loss cost are always occurring simultaneously. So it is reasonable that the failure and process mean shift should be dealt with at the same time in determining the maintenance time. This study proposes a model that integrates both of them. In order to reflect the actual production system more accurately, this integrated model includes the items of process variance function and the loss function according to wear level.

• 한국관개배수논문집
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• 제18권2호
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• pp.142-160
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• 2011

This study was performed to apply the preventive management technique that is known for more economic and preventive for disaster than corrective technique to Repair & Improvement(R&I) Project policy of irrigational facilities. The appropriate periods of R&I Project had been driven to 40yrs, 24yrs, 27yrs, and 29yrs for reservoir, Pumping and drainage pumping station, Diversion weir and Irrigation & drainage canal respectively. The cost of R&I Project for 10 years had been estimated as 616.9 billion won per year including the 85 billion won for the project of 'Disaster prevention and Function continuity'. After the period of 'Improvement all at once', about 30yrs, 421.8 billion won was requested for 'Function continuity'.

• 대한기계학회논문집A
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• 제34권9호
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• pp.1325-1330
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• 2010

터빈설비 각 중요부품의 고장은 발전정지라는 큰 파급효과를 유발하며, 예기치 못한 고장으로 설비의 이용률이 감소하게 되면 막대한 경제적 손실이 발생한다. 현재 발전설비는 제작사에서 제시한 정비주기를 기준으로 보수적인 예방정비를 실시하고 있으나, 급변하는 경영환경에서 경쟁력을 유지하기 위해서는 신뢰도를 유지하면서 정비비용을 절감하는 신뢰도 기반 정비방법을 도입 해야 할 필요가 있다. 신뢰성 있는 정비주기를 선정하기 위해서는 설비의 고장이력에 대한 면밀한 분석을 통하여 고장확률을 예측해야 한다. 본 논문은 발전설비 중 터빈 각 부품들의 고장이력을 데이터베이스로 만들고, Weibull 함수를 이용하여 최적의 정비시점을 예측하며, 정비주기를 결정하는 방법에 대하여 연구하였다.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.145-153
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• 2017

Systemic management is required at each phase of the C4I system life cycle to achieve information advantage in the battlefield through stable operation of the C4I system under the NCOE. In particular, the maintenance phase is the longest period of the C4I system life cycle, and it is easy to utilize and analyze data such as faults that occur during system operation. However, according to the previous research, the maintenance is evaluated as a phase in which the definition and management of comprehensive indicators are insufficient compared to other phase. In this paper, we propose the method of C4I Maintenance Priority decision using Maintenance metric. As a result of modifying the Naval Tactical C4I System's preventive maintenance cycle according to the priority, the total number of faults is reduced and the maintenance efficiency is improved.

• 산업경영시스템학회지
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• 제38권3호
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• pp.100-107
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• 2015

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

• Communications for Statistical Applications and Methods
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• 제15권1호
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• pp.77-86
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• 2008

본 논문에서는 비재생보증이 종료된 이후의 최적의 주기적인 예방보전정책을 제안한다. 비재생보증기간이 종료된 이후의 예방보전에 대하여 Wu와 Clements-Croome (2005)의 확률적 보전효과를 갖는 주기적인 예방보전모형을 가정한다. 시스템의 운영 기간 동안 사용자가 지불하여 야 할 비용들이 주어져 있을 때 단위시간당 기대비용을 결정한다. 또한, 구해진 단위시간당 기대비용을 최소화하는 최적의 예방보전 주기와 횟수를 결정하는 방법을 다룬다. 마지막으로 본 논문에서 제안된 예방보전정책을 설명하기 위해서 수치적 예를 살펴본다.

• Journal of Preventive Medicine and Public Health
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• 제45권4호
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• pp.219-226
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• 2012

Objectives: To evaluate the risk of fractures related with zolpidem in elderly insomnia patients. Methods: Health claims data on the entire South Korean elderly population from January 2005 to June 2006 were extracted from the Health Insurance Review and Assessment Service database. We applied a case-crossover design. Cases were defined as insomnia patients who had a fracture diagnosis. We set the hazard period of 1 day length prior to the fracture date and four control periods of the same length at 5, 10, 15, and 20 weeks prior to the fracture date. Time independent confounding factors such as age, gender, lifestyle, cognitive function level, mobility, socioeconomic status, residential environment, and comorbidity could be controlled using the case-crossover design. Time dependent confounding factors, especially co-medication of patients during the study period, were adjusted by conditional logistic regression analysis. The odds ratios and their 95% confidence intervals (CIs) were estimated for the risk of fracture related to zolpidem. Results: One thousand five hundred and eight cases of fracture were detected in insomnia patients during the study period. In our data, the use of zolpidem increased the risk of fracture significantly (adjusted odds ratio [aOR], 1.72; 95% CI, 1.37 to 2.16). However, the association between benzodiazepine hypnotics and the risk of fracture was not statistically significant (aOR, 1.00; 95% CI, 0.83 to 1.21). Likewise, the results were not statistically significant in stratified analysis with each benzodiazepine generic subgroup. Conclusions: Zolpidem could increase the risk of fracture in elderly insomnia patients. Therefore zolpidem should be prescribed carefully and the elderly should be provided with sufficient patient education.