• Transactions of the Korean Society of Automotive Engineers
• /
• v.18 no.1
• /
• pp.31-36
• /
• 2010

Collecting all failures during life cycle of vehicle is not easy way because its life cycle is normally over 10 years. Warranty period can help gathering failures data because most customers try to repair its failures during warranty period even though small failures. This warranty data, which means failures during warranty period, can be a good resource to predict initial reliability and permanence reliability. However uncertainty regarding reliability prediction remains because this data is censored. University of Wuppertal and major auto supplier developed the reliability prognosis model considering censored data and this model introduce to predict reliability estimate further "failure candidate". This paper predicts reliability of telecommunications system in vehicle using the model and describes data structure for reliability prediction.

• Journal of Applied Reliability
• /
• v.11 no.4
• /
• pp.387-398
• /
• 2011

$217Plus^{TM}$, a newly developed as a surrogate of the MIL-HDBK-217, may be widely applied for reliability predictions of electronic systems. In this study, we performed sensitivity study of the $217Plus^{TM}$ system model to various parameters. Specific attention was put to logistics model and its behavior has been examined in terms of non-component failure causes. We first briefly explained the $217Plus^{TM}$ methodology with system level failure rate evaluation. We then applied experimental designs with several failure causes as factors. We used an orthogonal array with three levels of each parameter. Our results indicate that cannot duplicate, induced, and wear-out causes have dominant effects on the system failures and design, parts, and system management have much less but a little strong effects. The results in this study not only figure out the behavior of the predicted failure rate as functions of failure causes but provide meaningful guidelines for practical applications.

• Journal of Applied Reliability
• /
• v.11 no.4
• /
• pp.433-445
• /
• 2011

Duty cycle is determined as the ratio of operating time to total time. Duty cycle in reliability prediction is one of the significant factors to be considered. In duty cycle application, non-operating time failure rate has been easily ignored even though the failure rate in non-operating period has not been proved to be small enough. Ignorance of non-operating time failure rate can result in over-estimated system reliability calculation. Furthermore, utilization of duty cycle in reliability prediction has not been evaluated in its effectiveness. In order to address these problems, two reliability models, such as MIL-HDBK-217F and RIAC-HDBK-217Plus, were used to analyze non-operating time failure rate. This research has proved that applying duty cycle in 217F model is not reasonable by the quantitative comparison and analysis.

• Journal of Distribution Science
• /
• v.17 no.11
• /
• pp.73-79
• /
• 2019

Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

• Journal of Applied Reliability
• /
• v.17 no.2
• /
• pp.92-102
• /
• 2017

Purpose: Reliability prediction standards consider environmental conditions, such as temperature, humidity and vibration in order to predict the reliability of the electronics components. There are many types of standards, and each standard has a different failure rate prediction model, and requires different environmental conditions. The purpose of this study is to make a sensitivity analysis by changing the temperature which is one of the environmental conditions. By observing the relation between the temperature and the failure rate, we perform the sensitivity analysis for standards including MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES. Methods: we establish environmental conditions in accordance with maneuver weapon systems's OMS/MP and mission scenarios then predict the reliability using MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES through the case of DC-DC Converter. Conclusion: Reliability prediction standards show different sensitivities of their failure rates with respect to the changing temperatures.

• Journal of Korean Society of Water and Wastewater
• /
• v.30 no.2
• /
• pp.155-165
• /
• 2016

Pipe Deterioration Prediction (PDP) and Pipe Failure Risk Prediction (PFRP) models were developed in an attempt to predict the deterioration and failure risk in water mains using fuzzy technique and the markov process. These two models were used to determine the priority in repair and replacement, by predicting the deterioration degree, deterioration rate, failure possibility and remaining life in a study sample comprising 32 water mains. From an analysis approach based on conservative risk with a medium policy risk, the remaining life for 30 of the 32 water mains was less than 5 years for 2 mains (7%), 5-10 years for 8 (27%), 10-15 years for 7 (23%), 15-20 years for 5 (17%), 20-25 years for 5 (17%), and 25 years or more for 2 (7%).

• The Journal of Information Systems
• /
• v.16 no.3
• /
• pp.1-20
• /
• 2007

Most researches on the corporate credit rating are generally classified into the area of bankruptcy prediction and bond rating. The studies on bankruptcy prediction have focused on improving the performance in binary classification problem, since the criterion variable is categorical, bankrupt or non-bankrupt. The other studies on bond rating have predicted the credit ratings, which was already evaluated by bond rating experts. The financial institute, however, should perform effective loan evaluation and risk management by employing the corporate credit rating model, which is able to determine the credit of corporations. Therefore, this study presents a corporate credit rating method using business failure probability map(BFPM) and AHP(Analytic Hierarchy Process). The BFPM enables us to rate the credit of corporations according to business failure probability and data distribution or frequency on each credit rating level. Also, we developed AHP model for credit rating using non-financial information. For the purpose of completed credit rating model, we integrated the BFPM and the AHP model using both financial and non-financial information. Finally, the credit ratings of each firm are assigned by our proposed method. This method will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings.

• Journal of Applied Reliability
• /
• v.13 no.1
• /
• pp.65-76
• /
• 2013

In order to assess the reliability of engine mount for a vehicles, life test model and procedure are developed. By using this method, failure mechanism and life distribution are analyzed. The main results are as follows; i) the main failure mechanism is degradation failure of engine mount rubber by fatigue failure at dynamic load. ii) temperature is a second factor to affect a failure. iii) the life distribution of engine mount module is fitted well to Weibull life distribution and the shape parameter is 18.4 and the accelerated life model of that is fitted well to Arrhenius model.

• Journal of Mechanical Science and Technology
• /
• v.19 no.6
• /
• pp.1280-1289
• /
• 2005

This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.1749-1753
• /
• 2007

The reliability, that is Long-Term Quality, require an approaching different from Short-Term Quality which is used before. As the electronic components are able to be easily normalized on the reliability testing, various testing standards are used. In this study, we proposed two reliability simulator that is PoF(Physics of Failure)-based and failure rate models-based. PoF-based simulator is introduced based on CalceEP program that is created by University of Maryland. This simulator can be modified by user interface of properties and PoF models and operated on stand alone system. Failure rate models-based simulator introduced according to analyzing reliability prediction documents. Also, unified database including failure data models is built from existing MIL-HDBK-217F N2, PRISM, and Bellcore, and web-based simulator is developed. The developed reliability simulator will service of the PoF model, properties, failure rate model accumulated and its data by web and internet.