• Journal of Korean Society for Quality Management
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• v.35 no.4
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• pp.140-146
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• 2007

In this paper, we consider a periodic imperfect preventive maintenance(PM) policy in which the system's failure rate after each PM remains unchanged. The system undergoes only minimal repairs at failures between PMs. Exact mathematical formula of the expected cost rate per unit time is derived. Optimal number of PMs and optimal maintenance period are derived by minimizing the expected cost rate per unit time. A numerical example is provided to illustrate the proposed approach under Weibull lifetime distribution.

• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.53-65
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• 2002

This paper studies an economic manufacturing quantity (EMQ) model with two types of failures and planned preventive maintenance of the production facility. One is a type I (major) failure which should be corrected by a failure maintenance and the other is a type H (minor) failure which can be minimally repaired without interrupting the production run. The objective is to determine the lot size and preventive replacement policy minimizing the long-run expected cost per unit time. We consider a control policy with a constant production lot size and preventive maintenance after completing n production runs. It is assumed that both preventive and failure maintenance times are random and the demand arriving during a stock-out period is lost. An expression for the expected cost per unit time is obtained in the general case. A special case is discussed and numerical results are provided.

• Journal of Korean Society for Quality Management
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• v.41 no.4
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• pp.693-708
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• 2013

Purpose: This study is to develop an evaluation model for analysis of CMMS Implementation status and provide CMMS advancement methods to maximize implementation effect through the evaluation model. Methods: After extracting common modules from CMMS packages and establishing evaluation standard for each module, then the evaluation standard is applied to 33 Korean companies for evaluating their own current implementation status. Results: Preventive maintenance and analysis information modules were considered the most vulnerable in Korean companies which have introduced CMMS packages. And the reason why preventive maintenance is vulnerable is that there is poor build-up of their own preventive maintenance standards. Conclusion: Korean companies which will introduce CMMS need to make preventive maintenance standards, and data of the materials and the equipment to improve the effectiveness in advance.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.1
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• pp.34-42
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• 2019

Ten AOC(Air Operation Certificate) holders certified by MOLIT of Korea are operating their own maintenance training program. Though the maintenance training program is approved by the same authority, the contents of the program are different even in the mandatory training courses among AOC holders. The survey interview showed that the maintenance training in mandatory training should have the same contents and requirements. Throughout the survey and focus group discussion, this paper suggests the list and contents of the initial mandatory training and the list, contents and interval for the recurrent mandatory training. This paper also suggests how to implement the on-line training program for recurrent mandatory training to keep the quality of the airline maintenance training program.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.171-175
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• 2007

The Service sector has increased in importance over the last decade in troops. Military included public sector, but has very different peculiarity from other public institution. So it's necessary that developing an evaluation tool that measuring service quality and customer satisfaction for troops. This study was conducted to identify tile service quality factors which are utilized to measure military vehicle maintenance service quality and customer satisfaction. In this paper, developing a Structural Equation Model at 'three dimensional model of service quality', and it is applied to customers of military vehicle maintenance service.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.247-251
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• 1998

From the early 90's TPM(Total Productive Maintenance) plays important roles to improve productivity and quality to keep enterprise's competivity. This study presents the results of an enquiry for the maintenance management of Korean industry in 1996. The response rate was 35.8% (43 companies) that the corporations were divided into four industrial groups, heavy process, light process, heavy assembly and light assembly. 40 question were asked, including maintenance organization, maintenance personnel, maintenance cost, measurement of maintenance performance and improvements achieved. This paper compares the results with those of an earlier Japanese and British enquiry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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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.

• 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.