• International Journal of Railway
• /
• v.1 no.2
• /
• pp.59-63
• /
• 2008

The maintenance effect is a peculiar factor applied to repairable systems such as rolling stocks. Conventional statistical analysis for failure times takes into account one of the two following extreme assumptions, namely, the state of the system after maintenance is either as "good as new" (GAN, perfect maintenance model) or as "bad as old" (BAO, minimal maintenance model). Most of the papers concerning the stochastic behavior of railroad systems assume two types of maintenance: perfect and minimal maintenance. However, Lee, Kim & Lee (2008) analyzed the failure data of a door system in Metro EMU and the effect of preventive maintenance was imperfect. It is seen that the imperfect maintenance is of great significance in practice. This article describes how to deal with the maintenance effect in reliability studies of rolling stocks. Maintenance policies under imperfect maintenance are described and the method is proposed to evaluate their performance.

• Journal of the Korean Society for Railway
• /
• v.14 no.3
• /
• pp.216-221
• /
• 2011

An important problem in reliability analysis for repairable systems is to model the maintenance effect. The most of researches have assumed two extreme cases; one is perfect maintenance and the other is minimal maintenance. However, many of maintenances performed by domestic subway operators are imperfect maintenances which have the effect between both of two extreme cases. This article deals with the problem determining the imperfect preventive maintenance intervals based on failure data in units of the PDS(passenger door system) in Metro EMU. This paper deals with a case study on determining imperfect maintenance interval by using the level of maintenance effect through reliability analysis of PDS.

• Proceedings of the KIEE Conference
• /
• 2006.11a
• /
• pp.9-11
• /
• 2006

This paper suggests a revision method for historical fault data using Proportional Aging Reduction(PAR) to consider maintenance effect in time-varying failure rate. In order to product time-varying failure rate, the historical fault data are necessary. However, the maintenance record could be left out in historical data by spot operator's mistake. In this case, the failure rate is produced less than the average failure rate for increasing equipments' life-time by maintenance effect. Hence, it is necessary for new time-varying failure rate to extract maintenance effect from the existing fault data. In this paper, the revision method to reduce equipments' life-time, adversely using PAR among three techniques to consider maintenance effect.

• Proceedings of the KSR Conference
• /
• 2008.06a
• /
• pp.733-741
• /
• 2008

An important problem in reliability analysis for repairable systems is to model the maintenance effect. The most of researches have assumed two extreme cases; one is perfect maintenance and the other is minimal maintenance. However, there are many cases in real situations that the maintenance effect are between both of two extreme cases. This article deals with the problem determining the imperfect preventive maintenance intervals for the doors in Metro EMU

• Journal of Information Technology Services
• /
• v.20 no.4
• /
• pp.23-33
• /
• 2021

The prolonged coronavirus 19 (COVID-19) has caused serious problems such as job losses and youth unemployment, but as the fourth industrial revolution and digital transformation accelerate, the importance of SW is highlighted and more qualified jobs are expected in the SW industry. However, domestic SW companies are having difficulties in not properly recognizing the value of SW products. Among many related issues, commercial SW maintenance-related issues are representative, and the main problem is the difference in the maintenance fee rates between domestic and foreign SW. In this study, the expected job creation effect when the SW maintenance rate is raised was analyzed using data related to the SW industry and commercial software. As a result of the analysis, the amount required to raise the commercial SW maintenance rate by 1% is 162 billion won. If all of these are used for employment, the expected new job creation effect is 3,240 jobs per year, and 15,451 jobs are created per year when calculated and estimated as the effect of increasing sales through the employment inducement coefficient. In addition, the amount required to raise the current average maintenance rate of 11.1% to 15% is 631.9 billion won, and it was possible to estimate the effect of creating jobs for 12,648 people based on the simple average wage and 60,259 people from the sales increase effect.

• Proceedings of the KSR Conference
• /
• 2008.11b
• /
• pp.1539-1544
• /
• 2008

There is a existing study dealing with the case that the effect of preventive maintenances to restore the door system is imperfect. When the effect of the preventive maintenance is imperfect, we need to consider the maintenance effect for making reliable and economical maintenance policies. The maintenance policies applicable for imperfect maintenance cases are considered and their effectiveness are evaluated through simulation in cases of passenger door system:PDS.

• Proceedings of the Safety Management and Science Conference
• /
• 2011.11a
• /
• pp.123-133
• /
• 2011

This paper reviewed the relationship between job stress and human error, and the moderating effect of age and maintenance type on the relationship between job stress and human error in maintenance personnel. Based on the responses from 450 maintenance personnels, the results of multiple regression analysis showed that physiological and psychological stress responses have positively related with human error. In moderating effect test, age appeared to impact on the relationship between physiological/behavioral stress and human error.

• Journal of Applied Reliability
• /
• v.17 no.3
• /
• pp.256-263
• /
• 2017

Purpose: This article provides the efficiency test results of conducting depot maintenance. Method: ANOVA (analysis of variance) and ANCOVA (analysis of covariance) tests are conducted using data obtained from Defense Logistics Integrated Information System (DELIIS). Results: The result shows that although the effect of the depot maintenance is significant, some parts do not follow the overall effect of the depot maintenance. In order to solve the problem we provide some suggestions to be improved. Conclusion: For improving the combat readiness condition of K-1 main battle tank, the maintenance policies and regulation must be revised for the parts of the weakness. In addition, the collection way of the operation and maintenance data must be redesigned.

• Journal of Applied Reliability
• /
• v.1 no.1
• /
• pp.47-54
• /
• 2001

This paper considers the parameter estimation problem of the failure intensity function and maintenance effect in a repairable system. We propose estimation procedures for repairable systems on which preventive maintenance is performed. The failure process is modeled by a proportional age reduction model [Brown, Mahoney and Sivazlian(1983)] which is useful to model the imperfect effect of preventive maintenance. When failure and maintenance (preventive) times are given, the maximum likelihood method is used to estimate the maintenance effect and the parameters of intensity function, simultaneously We obtain the maximum likelihood estimators using a genetic algorithm. A numerical example is also presented.

• International Journal of Reliability and Applications
• /
• v.9 no.1
• /
• pp.113-122
• /
• 2008

In this paper, we consider a periodic preventive maintenance policy in which each preventive maintenance reduces the hazard rate of amount proportional to the failure intensity, which increases since the system started to operate. And the effect of preventive maintenance at each preventive maintenance epoch is different. The expected cost rate per unit time for the proposed model is obtained. We discuss the optimal number N of the periodic preventive maintenance and the optimal period x, which minimize the expected cost rate per unit time and obtain the optimal preventive maintenance schedule for given cost structures of the model. A numerical example is given for the purpose of illustrating our results when the failure time distribution is Weibull distribution.