• International Journal of Quality Innovation
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• v.7 no.3
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• pp.15-23
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• 2006

A spare ordering policy is considered for planned maintenance. Introducing the ordering, uptime, downtime, inventory costs and salvage value, we derive the expected cost effectiveness. The problem is to determine jointly the ordering time for a spare and the preventive replacement time for the operating unit which maximize the expected cost effectiveness. Some properties regarding the optimal policy are derived, and a numerical example is included to explain the proposed model.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.193-204
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• 2003

In this paper, we consider a periodic preventive maintenance(PM) policy in which each PM reduces the hazard rate but remains the pattern of hazard rate unchanged. And the system undergoes only minimal repairs at failures between PM's. The expected cost rate per unit time is obtained. The optimal number N of PM and the optimal period x, which minimize the expected cost rate per unit time are discussed. Explicit solutions for the optimal periodic PM are given for the Weibull distribution case.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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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.

• Journal of Aerospace System Engineering
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• v.15 no.6
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• pp.66-71
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• 2021

With the exception of some large domestic airlines with adequate maintenance capability, most low-cost and small airlines do not have the facilities, equipment/tools, or manpower to perform periodic inspections over "C check." They are repaired according to maintenance programs specified by manufacturers. The outsourcing (domestic or overseas) of maintenance contracts is thus crucial to achieve good quality service at low cost, and these contracts therefore need to be signed with a full understanding of what is to be expected. This study aims to determine the requirements to be considered prior to finalizing such contracts.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.108-116
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• 2010

The maintenance of a deteriorating system is often imperfect. Previous studies have shown that the imperfect preventive maintenance (PM) can reduce the wear out and aging effects of deteriorating systems to a certain level between the conditions of as good as new and as bad as old. In this paper, we employ the concept of the improvement factor in investigating two optimal PM policies; failure limit policy and periodic PM policy. We redefine the improvement factor model as a function of the cost of PM, using this concept, we derive the conditions of optimal PM policies and formulate expressions to compute the expected cost rate. Based on this information, the determination of the maintenance policies which minimize the cost rate is examined. Numerical examples for the Weibull distribution case are also given.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.22-24
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• 2006

The installations of power quality monitoring system have increased drastically over the past several decades. These systems have been effectively used to monitor, analyze and diagnose the conditions of power system, and furthermore can be used to improve the present asset maintenance policy, scheduled (time-based) method, into the advanced, cost-effective and labor-effective maintenance methods, such as condition-based maintenance, predictive maintenance and reliability centered maintenance. As an approach to this, this paper introduces the statistical methods, three kinds of control charts (Shewhart chart, CUSUM chart and EWMA chart), and discusses the applicability of these methods to recognize the changing trends of power quality indices and to estimate the system's condition, using Matlab.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.143-149
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• 2018

The purpose of this study is to propose a management method to maintain the pleasant indoor air quality of the dental clinic by measuring and analyzing the indoor air quality of the dental clinic. The measurement was conducted in two rooms, a lobby where many residents stay in the reception room for waiting for medical treatment, and a VIP room where treatment activities are mainly performed. Measurement items are Temperature, Humidity, $CO_2$, CO, $NO_2$, $CH_2O$, VOC, $PM_{10}$ and measurement were taken on April 27, 2018. As a result of analyzing the temperature and humidity of the dental clinic, it was analyzed that the average indoor temperature was maintained at $25^{\circ}C$ and the humidity was kept at around 50%, maintaining proper indoor temperature and humidity environment. $CO_2$ was 855ppm in the VIP Room, which satisfied the maintenance standard. In the case of the lobby, it was analyzed to be 1,160ppm, which exceeded the maintenance standard and it is judged that the carbon dioxide generated by the respiration of the people staying in the lobby is the main reason. The mean concentration of formaldehyde in the VIP room was analyzed as $436{\mu}g/m^3$, exceeding the maintenance standard, and $2,100{\mu}g/m^3$ for the VOC exceeded the recommended standard. It was analyzed that the concentration was relatively higher due to the use of disinfectant and other drugs. The mean concentration of PM-10 in the lobby was analyzed as $65{\mu}g/m^3$ and it was analyzed that it satisfied the maintenance standard. To maintain a pleasant indoor air quality in a dental clinic it is necessary to minimize the effects of formaldehyde, VOC, $CO_2$ in the VIP rooms and lobby. For this purpose, the entire ventilation system and air purification system of the dental clinic should be installed. In case of the VIP room, local exhaust ventilation should be installed and workers should wear personal protective equipment.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.315-327
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• 2023

Purpose: Recently, research has continued to predict the time of failure of the facility through measurement data obtained by attaching a sensor to the facility. However, depending on the facility, it may be difficult to attach a sensor. The purpose of this study is to propose a power generation maintenance plan system based on failure record data obtained from Continuous Ship Unloader, one of the facilities that is difficult to attach sensors. Methods: This study uses data collected from 2012 to 2022 from the 'CSU-1B' model among Continuous Ship Unloader operated by Korea Midland Power Co., LTD. By fitting fault record data to the Weibull distribution, appropriate maintenance cycles and ranges for each target facility subsystem are derived. In addition, maintenance group between subsystems is selected through Euclidean distance, a metric often used for time series data similarity. Through this, a system for establishing an maintenance plan for power generation facilities is proposed. Results: The results of this study are as follows. For the 17 subsystems of the Continuous Ship Unloader, proper maintenance cycles and ranges were determined, and a total of four maintenance groups were chosen. This resulted in the creation of an power generation maintenance plan system and the establishment of an maintenance plan. Conclusion: This study is a case study of power generation facilities. We proposed a maintenance plan system for Continuous Ship Unloader among power generation facilities.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.109-113
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• 2004

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.82-88
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• 2018

The decoy defensive weapon system is a one-shot system. Reliability is maintained through periodic inspection and high reliability is required to confirm whether or not the functioning is normal after launch. The maintenance cycle of a decoy was set up without target reliability and reliability prediction during the development period. However, the number of operations in the military has been increasing, necessitating the optimization of the maintenance cycle. Reliability is analyzed using the maintenance data of a decoy operated for several decades and the optimal maintenance cycle is suggested. In chapter 2, data collection and classification methods are presented and analysis methodology is briefly introduced. In chapter 3, the data distribution analysis and fitness verification confirmed that applying the Weibull distribution is the most suitable for the maintenance data of the decoy. In chapter 4, we present the analysis result of percentile, survival probability and MTBF and the optimal maintenance cycle was derived from the reliability analysis. Finally, we suggest the application methods for this paper in the future.