• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.133-136
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• 2003

In these days, the reliability analysis and prediction are applied for many industrial products and many products require guaranteeing the quality and efficiency of their products. In this study reliability prediction for core units of machine tools has been performed in order to improve and analyze its reliability. ATC(Automatic Tool Changer) and interface Card of PC-NC that are core component of the machine tools were chosen as the target of the reliability prediction. A reliability analysis tool was used to obtain the reliability data(failure rate database) for reliability prediction. It is expected that the results of reliability prediction be applied to improve and evaluate its reliability. Failure rate, MTBF (Mean Time Between Failure) and reliability for core units of machine tools were evaluated and analyzed in this study.

• 대한안전경영과학회지
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• 제10권3호
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• pp.81-87
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• 2008

The reliability prediction and evaluation for general electronic components are required to guarantee in quality and in efficiency. Although many methodologies for predicting the reliability of electronic components have been developed, their reliability might be subjective according to a particular set of circumstances, and therefore it is not easy to quantify their reliability. In this study reliability prediction of electronic components, that is the interface card, which is used in the CNC(Computerized Numerical Controller) of machine tools, was carried out using PRISM reliability prediction specification. Reliability performances such as MTBF(Mean Time Between Failure), failure rate and reliability were obtained, and the variation of failure rate for electronic components according to temperature change was predicted. The results obtained from this study are useful information to consider a counter plan for weak components before they are used.

• 한국시뮬레이션학회논문지
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• 제25권4호
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• pp.77-84
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• 2016

본 논문은 시스템에 대한 기능 중심의 신뢰도 예측을 수행하기 위한 모델링 방법론을 제안한다. 신뢰도 예측에 대한 다양한 기존 연구들이 있지만, 이 연구들의 공통점은 하드웨어 중심으로 신뢰도 예측을 수행하였다는 점이다. 신뢰성이 제품이 주어진 사용 조건 아래서 의도하는 기간 동안 정해진 기능을 성공적으로 수행하는 능력이라고 정의되는 점에서 보았을 때, 하드웨어 중심의 신뢰도는 논리적 모순을 가진다. 본 논문에서는 기능 중심의 신뢰도 예측을 위해 4-단계 모델링 절차(four-phase modeling procedure)를 제안하였다. 제안되는 모델링 방법론은 네 개의 모델로 구성된다; 1) 구조적 블록 모델(structure block model), 2) 기능 블록 모델 (function block model), 3) 장치 모델 (device model), 그리고 4) 신뢰성 예측 모델 (reliability prediction model). 본 논문에서는 제안하는 모델링 방법론을 이용하여 전자식 안정기에 대한 기능 중심의 신뢰도 예측을 수행하였으며, 하드웨어의 신뢰도를 결정하기 위해 신뢰도 예측 규격 중 하나인 MIL-HDBK-217F를 이용하였다.

• 한국신뢰성학회지:신뢰성응용연구
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• 제11권4호
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• pp.399-407
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• 2011

Reliability evaluation of One-Shot system which flies at speed of Mach must be evaluated as the result of many firing tests. But many firing tests are impossible because of budget deficit. Consequently the reliability prediction which substitutes firing tests is used. The accuracy of reliability prediction is decided according to a quantity of accumulated test data. If the test data is insufficient, the direction of prediction can not be set. So we propose the reliability prediction method which applies MIL-HDBK-217 Plus. MIL-HDBK-217 Plus is described about reliability prediction method without sufficient test data. So we apply MIL-HDBK-217 Plus to the rocket motor system, and we accomplish a modeling and a reliability prediction about the system.

• 산업공학
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• 제21권1호
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• pp.85-95
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• 2008

Reliability prediction serves many purposes during the life of a system, so several methods have been developed to predict the parts and systems reliability. MIL-HDBK-217F, among the those methods, has been widely used as a requisite tool for the reliability prediction which is applied to nuclear power plants and their safety regulations. This paper presents the reliability prediction for the DSP(Digital Signal Processor) module composed of three assemblies. One of the assemblies has a monitoring and self test function which is used to enhance the module reliability. The reliability of each assembly is predicted by MIL-HDBK-217F. Based on these predicted values, Markov modelling is finally used to predict the module reliability. Relax 7.7 software of Relax software corporation is used because it has many part libraries and easily handles Markov processes modelling.

• 품질경영학회지
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• 제47권1호
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• pp.187-198
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• 2019

Purpose: In this study, a reliability prediction based reliability growth management is suggested especially for the early development phase of a system and the case study of surveillance system is given. Methods: The proposed reliability prediction based reliability growth management procedures consists of 7 Steps. In Step 1, the stages for reliability growth management are classified according to the major design changes. From Step 2 to Step 5, system reliability is predicted based on reliability structures and the predicted reliabilities of subsystems (Level 2) and modules (Level 3). At each stage, by comparing the predicted system reliability with that of the previous stage, the reliability growth of the system is checked in Step 6. In Step 7, when the predicted value of sustem reliability does not satisfy the reliability goal, some design alternatives are considered and suggested to improve the system reliability. Results: The proposed reliability prediction based reliability growth management can be an efficient alternative for managing reliability growth of a system in its early development phase. The case study shows that it is applicable to weapon system such as a surveillance system. Conclusion: In this study, the procedures for a reliability prediction based reliability growth management are proposed to satisfy the reliability goal of the system efficiently. And it is expected that the use of the proposed procedures would reduce, in the test and evaluation phase, the number of corrective actions and its cost as well.

• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• 한국안전학회지
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• 제27권4호
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• pp.115-120
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• 2012

In order to establish preventive maintenance standards through analysis & reliability prediction of about 60,000pcs of 20kindsof relays and contractors used for Seoul subway trains, several life prediction methodologies were applied. Firstly, Occurrence, Severity, Detection were defined and predicted by applying operation characteristic of EMU to the number of actions of relays & contactors which the manufacturers generally offer as the life cycle data. Secondly, failure distribution and average life of parts were analyzed through interpretation of field data based on a lot of experience which had built up in the field for a long time. Finally, using the 217PLUS standard as a reliability prediction program, comparative analysis of use reliability and inherent reliability was done through reliability prediction at the part level and system level.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권3호
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• pp.250-259
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• 2018

Purpose: Previously, missile reliability prediction is based on theoretical failure prediction model. It has shown that the predicted reliability is inadequate to real field data. Although an MTTF based reliability prediction method using real field data has recently been studied to overcome this issue. In this paper, we present a more realistic method, considering MTBF concept, to predict missile reliability. Methods: In this paper we proposed a modified survival model. This model is considering MTBF as its core concept, and failed missiles in the model are to be repaired and redeployed. We compared the modified model (MTBF) and the previous model (MTTF) in terms of fitness against the real failure data. Results: The reliability prediction result of MTBF based model is closer to fields failure data set than that of MTTF based model. Conclusion: The proposed MTBF concept is more fitted to real failure data of missile than MTTF concept. The methodology of this study can be applied to analyze field failure data of other similar missiles.

• 한국철도학회논문집
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• 제9권5호
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• pp.601-605
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• 2006

Reliability of the Railway signaling system which is safety critical is determined by reliability of hardware and software. Reliability of hardware is easily predicted and demonstrated through lots of different studies and environmental tests, while that of software is estimated by the iterative test outcomes so estimates of reliability will depend on the inputs. Combinations of inputs to and outputs from the software may be mostly combinatoric and therefore all the combinations could not be tested. As a result, it has been more important to calculate reliability by means of a simpler method. This paper identifies the reliability prediction equation applicable to reliability prediction for railway signaling system software, and performs the simulation of onboard equipment of automatic train control for high speed train to review reliability prediction and validity.