• Journal of Applied Reliability
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• v.15 no.2
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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.

• Journal of Applied Reliability
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• v.5 no.3
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• pp.381-391
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• 2005

The level of reliability attained largely depends upon the investment in reliability growth programs during development phase. In order to find the relationship between reliability growth test time and BRTE(basic reliability tasks effectiveness) in a reliability improvement program that minimizes LCC in which contains the reliability growth cost, repair and replacement costs, and spare parts ordering costs in service with given service rate in management policy, the growth rate has been suggested proper LCC versus growth rate. This model employs the reliability growth projection with delayed fixes in avionic equipment based on AMSAA.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.110-121
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• 2004

There is a new trend of incorporating software coverage metrics into software reliability modelling. This paper proposes a coverage-based software reliability growth model. Firstly, the failure rate function in coverage is analytically derived. Then it is shown that the number of detected faults follows a Nonhomogeneous Poisson distribution of which intensity function is the failure rate function in coverage. Practical applicability of the proposed models is examined by illustrative numerical examples.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.761-769
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• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• International Journal of Reliability and Applications
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• v.7 no.2
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• pp.155-166
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• 2006

Many software reliability growth models (SRGMs) based on nonhomogeneous Poisson process (NHPP) have been developed and applied in practice. NHPP SRGMs are characterized by their mean value functions. Mean value functions are usually derived from differential equations representing the fault detection/removal process during testing. In this paper such differential equations are regarded as frameworks for generating mean value functions. Currently available frameworks are theoretically discussed with respect to capability of representing the fault detection/removal process. Then two general frameworks are proposed.

• Journal of Applied Reliability
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• v.14 no.2
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• pp.129-136
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• 2014

Reliability test is focusing to detect the unexpected reliability failure and solve them for the high quality of products. The test data should be used to assess and project the current level of interesting product reliability and so it is very important to have the accurately assessing methodology with test data. There are two type of trend for test data as constant and changing one during testing and this paper shows the difference in the assessing results of these two cases. There is less information how to define the existence of reliability growth rate changing and calculate the parameters of the reliability growth models to make an accurate assessment with such condition, so i established the process and mathematical model to calculate the parameters at such condition to make reliability growth curve with high Goodness of Fit. I validated the new method with the data made from Monte Carlo Simulation and case from Demko (1993). Even the assessed result with the new methodology may be different with the case by case because of very diversity in test condition and testing product quality, but the process and method founded in this research can be applied to any case using Duane and AMSAA model for their test data assessment. I also present the evaluation method to see the effectiveness with new one which is a conventional knowledge and not popular to use, so it is possible to compare the results with the newly presented and conventional method for better business decision.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.143-146
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• 2005

The software reliability growth depends on the testing time because the failure rate varies whether it is long or not. On the other hand, it might be difficult to reduce failure rate for most of the cases are not available for debugging during operational phase, hence, there are some literatures to study that the failure rate is uniform throughout the operational time. The failure rate reduces and the reliability grows with time regardless of debugging. As a result, the products reliability varies with the time duration of these products in point of customer view. The reason of this is that it accumulates the products experience, studies the exact operational method, and then finds and takes action against the fault circumstances. I propose the simple model to represent this status in this paper.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.5
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• pp.11-16
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• 1998

We analyze the software reliability growth models for the specified period from the viewpoint of theory of differential equations. we defien a genralized form of reliability growth models as follws: dN(t)/dt = b(t)f(N(t)), Where N(t) is the number of remaining faults and b(t) is the failure rate per software fault at time t. We show that the well-known three software reliability growth models - Goel - Okumoto, s-shaped, and Musa-Okumoto model- are special cases of the generalized form. We, also, extend the generalized form into an extended form being dN(t)/dt = b(t, .gamma.)f(N(t)), The genneralized form can be obtained if the distribution of failures is given. The extended form can be used to describe a software reliabilit growth model having weibull density function as a fault exposure rate. As an application of the generalized form, we classify three mentioned models according to the forms of b(t) and f(N(t)). Also, we present a case study applying the generalized form.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.100-108
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• 2013

In aerospace industry, MTBF (Mean Time Between Failure) and MFTBF (Mean Flight Time Between Failure) are generally used for reliability analysis. So far, especially to Korean military aircraft, MFTBF of avionic equipments is predicted by MIL-HDBK-217 and MIL-HDBK-338, however, the predicted MFTBF by military standard has a wide discrepancy to that of real-world operation, which leads to overstock and increase operation cost. This study analyzes operational data of avionic equipments. Operational MFTBF, which is calculated from operational data, is compared with predicted MFTBF calculated conventionally by military standard. In addition, failure rate trend is investigated to verify reliability growth in operational data, the investigation shows that failure rate curve from operational data has somewhat pattern with decreased failure rate and constant failure rate.

• Journal of Applied Reliability
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• v.15 no.4
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• pp.248-255
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• 2015

Purpose : The purpose of this research is to develop the optimized method and process in the reliability-growth target setting, especially for complex and repairable system (or products) such as vehicle and airplane, construction equipment. Method : A reliability-growth test plan specifies a scenario to achieve the planned reliability value (or reliability target). The major elements in test planning are reliability-growth starting time and reliability level at that time, reliability-growth rate and reliability-growth target. All of them except a reliability target can be referred to the previous development data and reference researches. The reliability target level is directly influencing to test period (or time) which is related to test and warranty cost together. There are a few researches about the reliability target setting method and but showing the limitations to consider the views of engineering, business and customer together. There is no research how to handle the target setting process in detail. Result : We develop the optimized method and systematic process in reliability target setting with considering such views. This research also establish the new concept as production capability which means company (or supplier) capability to product its products. Conclusion : In this research result, we apply the new method to a few projects and can set the reasonable test planning. The developing results is showing the good balance between the developing cost and warranty cost at market.