• 한국신뢰성학회지:신뢰성응용연구
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• 제13권3호
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• pp.175-190
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• 2013

This study considers reliability growth management as the excellent method for construction equipment development with the effect on decreasing COPQ(Cost of Poor Quality Cost) of new products. MIL-HDBK-189A(1981) and RADC-TR-84-20(1984) standards provide a general concept of reliability growth management including to reliability growth test, models and FRACAS(Failure Reporting and Corrective Action System). There is no study how to apply reliability growth management to construction equipment(or machine) development. This paper propose the method to apply it to construction equipment development process from the reliability target setting for developing products to launching them at market. It is expecially showing how to set target reliability for new developing equipment and the development risk to reach the reliability target in detail.

• 한국신뢰성학회지:신뢰성응용연구
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• 제15권2호
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• pp.90-100
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• 2015

Reliability growth rate (or reliability growth curve slope) have the two cases of trend as a constant or changing one during the reliability growth testing. The changing case is very common situation. The reasons of reliability growth rate changing are that the failures to follow the NHPP (None-Homogeneous Poisson Process), and the solutions implemented during test to break out other problems or not to take out all of the root cause permanently. If the changing were big, the "Goodness of Fit (GOF)" of reliability growth curve to test data would be very low and then reduce the accuracy of assessing result with test data. In this research, we are using Duane model and AMSAA model for assessing test data and projecting the reliability level of complex and repairable system as like construction equipment and vehicle. In case of no changing in reliability growth rate, it is reasonable for reliability engineer to implement the original Duane model (1964) and Crow-AMSAA model (1975) for the assessment and projection activity. However, in case of reliability growth rate changing, it is necessary to find the method to increase the "GOF" of reliability growth curves to test data. To increase GOF of reliability growth curves, it is necessary to find the proper parameter calculation method of interesting reliability growth models that are applicable to the situation of reliability growth rate changing. Since the Duane and AMSAA models have a characteristic to get more strong influence from the initial test (or failure) data than the latest one, the both models have a limitation to contain the latest test data information that is more important and better to assess test data in view of accuracy, especially when the reliability growth rate changing. The main objective of this research is to find the parameter calculation method to reflect the latest test data in the case of reliability growth rate changing. According to my experience in vehicle and construction equipment developments over 18 years, over the 90% in the total development cases are with such changing during the developing test. The objective of this research was to develop the newly assessing method and the process for GOF level increasing in case of reliability growth rate changing that would contribute to achieve more accurate assessing and projecting result. We also developed the new evaluation method for GOF that are applicable to the both models as Duane and AMSAA, so it is possible to compare it between models and check the effectiveness of new parameter calculation methods in any interesting situation. These research results can reduce the decision error for development process and business control with the accurately assessing and projecting result.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2007년도 춘계학술대회
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• pp.335-346
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• 2007

This paper introduces reliability stress screening(RSS) for electronic hardware and components. This study also shows reliability centered maintenance(RCM), and reliability growth models. Moreover, this paper presents goodness-of-fit tests and estimation methods of power law model.

• 한국철도학회논문집
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• 제8권6호
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• pp.597-601
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• 2005

Korea Railroad Research Institute(KRRI) developed the Driverless Rubber Tired Korea-AGT(Model: K-AGT) from 1999 to 2004. We have finished the safety and performance tests of K-AGT. Data obtained from this testing can be used to evaluate the growth of reliability. The most widely used traditional growth tracking model is included as IEC International standard. With the tracking model all corrective actions are incorporated during test, called test-fix-test. In the test-fix-test strategy problem modes are found during testing and corrective actions for these problems are incorporated during testing. In this paper, we demonstrated reliability analysis using growth model of driverless rubber tired K-AGT system to prove reliability of development system. Therefore, we introduce the well-known NHPP model and analyze a reliability growth using ReliaSoft's RGA software.

• Nuclear Engineering and Technology
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• 제39권2호
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• pp.129-132
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• 2007

It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's non-homogeneous Poisson process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.305-312
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• 2016

Purpose: The purpose of this study is to provide a sensitivity analysis of system reliability for recognizing effectiveness of changing of BD mode failures using reliability growth projection model based on NHPP. Methods: Crow extended reliability projection model (CERPM) is used to analyze the changing of two factors 1) the number of BD mode failures, 2) fix effectiveness factor (FEF) values. Results: The system reliability has increased in accordance with the number of BD mode failures and FEF values have increased. Conclusion: It is necessary to design failure modes and FEF values to supervise the reliability.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권3호
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• pp.201-207
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• 2018

Purpose: To develop the reliability growth planning for a subsystem of guided weapon system using PM2-Continuous model. Methods: The target MTBF of the subsystem is set by allocating the system target MTBF to the lower level, where ARINC method is applied. Other model parameters such as initial MTBF, management strategy ratio and average fix effectiveness factor are chosen from historical growth parameter estimates. Given the values of model parameters, the reliability growth planning curve using PM2-Continuous model is constructed and the sensitivity analyses are performed for the changes of model parameters. Results: We have developed the reliability growth plan for a subsystem of guided weapon system using PM2-Continuous model. It was found that the smaller the ratio of initial MTBF to target MTBF, the smaller the management strategy ratio, the smaller the average fix effectiveness factor, and the shorter the development test period, the higher reliability growth is required. Conclusion: The result of this study will be used as a basis for establishing the reliability growth plan, the test period setting and the budget appropriation for the similar system entering the system development stage in the future.

• 산업경영시스템학회지
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• 제29권3호
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• pp.135-142
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• 2006

Engineers are always concerned with life cycle costs for making important economic decisions through engineering action like reliability of products. Decisions during the reliability growth development of products involve trade-offs between invested costs and its returns. In order to find minimal LCC containing the reliability improvement cost, production cost, repair and replacement costs, and holding cost of spare parts for failure items we suggest in this paper relationship between development cost and sustaining cost in values of growth parameter $\beta$ of AMSAA model. This model is applied to the reliability growth program based on AMSAA model during R&D phase, the warranty activities of items and the block replacement policy for maintenance of items in avionic equipment.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.157-161
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• 2023

Reliability is one of the computable quality features of the software. To assess the reliability the software reliability growth models(SRGMS) are used at different test times based on statistical learning models. In all situations, Tradational time-based SRGMS may not be enough, and such models cannot recognize errors in small and medium sized applications.Numerous traditional reliability measures are used to test software errors during application development and testing. In the software testing and maintenance phase, however, new errors are taken into consideration in real time in order to decide the reliability estimate. In this article, we suggest using the Weibull model as a computational approach to eradicate the problem of software reliability modeling. In the suggested model, a new distribution model is suggested to improve the reliability estimation method. We compute the model developed and stabilize its efficiency with other popular software reliability growth models from the research publication. Our assessment results show that the proposed Model is worthier to S-shaped Yamada, Generalized Poisson, NHPP.

• 한국신뢰성학회지:신뢰성응용연구
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• 제14권4호
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• pp.225-229
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• 2014

A one-shot device is defined as a product, system, weapon, or equipment that can be used only once. After use, the device is destroyed or must undergo extensive rebuild. Determining the reliability of a one-shot device poses a unique challenge to the manufacturers and users due to the destructive nature and costs of the testing. This paper presents a reliability growth prediction for a one-shot system. It is assumed that 1) test duration is discrete(i.e. trials or rounds); 2) trials are statistically independent; 3) the number of failures for a given system configuration is distributed according to a binomial distribution; and 4) the cumulative expected number of failures through any sequence of configurations is given by AMSAA model. When the system development is represented by three configurations and the number of trials and failures during configurations are given, the AMSAA model parameters and reliability at configuration 3 are estimated by using a reliability growth analysis software. Further, if the reliability growth predictions do not meet the target reliability, the sample size of an additional test is determined for achieving the target reliability.