• Journal of the Korean Solar Energy Society
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• v.39 no.4
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• pp.55-67
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• 2019

Recently, as the amount of particulate matter blowing from China increases, the domestic air environment is rapidly deteriorating. This pollution of the atmosphere greatly affects the light energy reaching the ground. Particularly, since the light enters the solar cell module in various forms, the amount of input energy of the solar power generation system may be changed depending on the ratio of direct beam irradiation and diffused horizontal irradiation. In this paper, we analyze how the ratio of direct beam component and diffused component on global horizontal irradiation varies with the atmospheric conditions. In addition, the reliability of the regression equation, designed to decompose the global horizontal irradiation into horizontal direct beam irradiation and diffused horizontal irradiation, was verified according to the level of air pollution. So, we derive the most suitable decomposition model for use in domestic climatic conditions in Korea by comparing the ratio of direct and diffuse component on the horizontal which is calculated with Perez model and Watanabe model using the meteorological weather data observed for 14 months. Finally, to reduce the error of the transposition result, we verified the reliability of the decomposition which depends on the atmospheric environment.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.4
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• pp.39-46
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• 2000

New products often have in-service reliability problem despite an intensive development program. Therefore reliability data must be collected and analyzed, and improvements designed and implemented. A type of reliability incentive contract which has recently attracted a lot of attention is reliability improvement warranty(RIW). It has been employed by military, airlines, telecommunication systems, and public utilities. An RIW contract requires that the supplies carries out all repairs, modify the equipment to improve its reliability, and provides all spates needed, for a fixed period, for once-off fee. This paper presents the reliability growth analysis and management methods for in-service MC68 microprocessor, which is the main component of the base station controller in PCS(Personal Communication Service) telecommunication system. The methods will provide guidelines to monitor reliability program in planning RIW contract.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.18-24
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• 2020

This research conducted an the failure analysis was performed based on the failure and operation data for Seven years using the Reliability, Availability, Maintainability, and Safety(RAMS) constructed at the operation stage after the opening of the D urban railway. therefore, the risk priority was selected for failure frequency component within the door system that showed high failure. Finally, the goal was to suggest ways to improve the door system. For this purpose, the analysis of thermal characteristics of failed components such as Door Control Unit(DCU) in the door system based on the Seven-year failure analysis data of RAMS was performed. These results were applied to the main component exchange cycle of the door unit, the mean time between failure(MTBF) and mean kilometer between failure(MKBF) values of RAMS increased by 26% in 2017-2018 when the improvement measures were taken, and the MTBF value of DCU was 300,000 hours, which was a 57% improvement in reliability. The results of this thesis identify potential enhancements in reliability and improvements in maintenance of the door system that, if implemented, would contribute to train safety and reduce instances of failure in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.194-202
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• 2019

Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

• Journal of Applied Reliability
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• v.16 no.4
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• pp.313-322
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• 2016

Purpose: We introduce ways to employ Markov chain model to evaluate the effect of preventive maintenance process. While the preventive maintenance process decreases the failure rate of each subsystems, it increases the downtime of the system because the system can not work during the maintenance process. The goal of this paper is to introduce ways to analyze this trade-off. Methods: Markov chain models are employed. We derive the availability of the system consisting of N repairable subsystems by the methods under various maintenance policies. Results: To validate our methods, we apply our models to the real maintenance data reports of military truck. The error between the model and the data was about 1%. Conclusion: The models developed in this paper fit real data well. These techniques can be applied to calculate the availability under various preventive maintenance policies.

• Proceedings of the Korean Reliability Society Conference
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• 2011.06a
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• pp.21-26
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• 2011

Initial reliability prediction done by calculation would be more practical if support by evidence from customer usage profile and field failure data to improve the prediction. Thus, the consistency of the design and the product would be practically validated. In this paper, it will address rationale and method to decide on Acceleration Factor (AF) to be used in Accelerated Life Test (ALT) through usage profile and field failure. The case study of tractor transmission is used to demonstrate the method which data obtained from surveys done on farmers, field visits and field failure data from service center. By considering all the elements, it will determine more relevant AF which indicates the real use conditions of the component.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.282-285
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• 1998

This paper presents a method to evaluate the effect of voltage sag in distribution system using the component reliability data of utilities. The proposed method is based on Specified CBEMA curve which is the probability curve of the customers' effect by voltage sag. We carried out the experiment for the customers' sensitive equipments using the test facilities in KERI. The Monte Carlo method and the historical reliability data in KEPCO are used for simulations.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.98-103
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• 2016

Purpose: The purpose of this paper is to get a meaningful information for improving manufacturing quality of the products before they are produced in client's manufacturing process. Methods: A variety of data mining techniques have been being used for wide range of industries from process data in manufacturing factories for quality improvement. One application of those is to get meaningful information from process data in manufacturing factories for quality improvement. In this paper, the failure rate at client's manufacturing process is predicted by using the parameters of the characteristics of the product based on PCA (Principle Component Analysis) and regression analysis. Results: Through a case study, we proposed the predicting methodology and regression model. The proposed model is verified through comparing the failure rates of actual data and the estimated value. Conclusion: This study can provide the guidance for predicting the failure rate on the manufacturing process. And the manufacturers can prevent the defects by confirming the factor which affects the failure rate.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.576-580
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• 2008

Rubber material properties and useful life evaluation are very important in design procedure to assure the safety and reliability of the rubber components. In this paper, the evaluation of characteristics and useful life prediction of rubber component for elevator cabin were experimentally investigated. The material test and accelerated heat-aging test were carried. Rubber material constants were obtained by curve fittings of simple tension, pure shear and bi-axial tension test data. Heat aging test results changes as the threshold are used for assessment of the useful life and time to threshold value were plotted against reciprocal of absolute temperature to give the Arrhenius plot. By using the rubber material and component test several useful life prediction equations for rubber component were proposed. Predicted useful life of rubber component for elevator cabin agreed fairly with the experimental lives.

• Plant Journal
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• v.12 no.2
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• pp.31-35
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• 2016

A method of failure data management for Reliability-Centered Maintenance was shown for a boiler feedwater pump of a power plant. The major part of it is an analysis of failure mode, failure cause, and failure effects, which is the main component of a failure data base like OREDA(Offshore Reliability Data). Case study shows main element of the preventive maintenance planning such as the maintenance period can be statistically determined from the failure data.