• Proceedings of the KWS Conference
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• 2006.05a
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• pp.30-32
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• 2006

The interfacial reaction and reliability of eutectic Sn-Pb and Pb-free eutectic Sn-Ag ball-grid-array (BGA) solders with an immersion Ag-plated Cu substrate were evaluated following isothermal aging at $150^{\circ}C$. During reflowing, the topmost Ag layer was dissolved completely into the molten solder, leaving the Cu layer exposed to the molten solder for both solder systems. A typical scallop-type Cu-Sn intermetallic compound (IMC) layer was formed at both of the solder/Cu interfaces during reflowing. The thickness of the Cu-Sn IMCs for both solders was found to increase linearly with the square root of isothermal aging time. The growth of the $Cu_3Sn$ layer for the Sn-37Pb solder was faster than that for the Sn-3.5Ag solder, In the case of the Sn-37Pb solder, the formation of the Pb-rich layer on the Cu-Sn IMC layer retarded the growth of the $Cu_6Sn_5$ IMC layer, and thereby increased the growth rate of the $Cu_3Sn$ IMC layer. In the ball shear test conducted on the Sn-37Pb/Ag-plated Cu joint after aging for 500h, fracturing occurred at the solder/$Cu_6Sn_5$ interface. The shear failure was significantly related to the interfacial adhesion strength between the Pb-rich and $Cu_6Sn_5$ IMC layers. On the other hand, all fracturing occurred in the bulk solder for the Sn-3.5Ag/Ag-plated Cu joint, which confirmed its desirable joint reliability.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.147-160
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• 2001

The reliability of computer software is of prime importance for all developers of software. The complicated nature of detecting and removing faults from software has led to a plethora of models for reliability growth. One of the most basic of these is the Jelinski Moranda model, where it is assumed that there are N faults in the software, and that in testing, bugs (or faults) are encountered (and removed when defected) according to a stochastic process at a rate which at a given point in time is proportional to the number of bugs remaining in the system. In this research, we consider the possibility that imperfect repair may occur in any attempt to remove a detected bug in the Jelinski Moranda model. We let p represent the probability that a fault which is discovered or detected is actually perfectly repaired. The possibility that the probability p may differ before and after release of the software is also considered. The distribution of both the number of bugs detected and perfectly repaired in a given time period is studied. Cost models for the development and release of software are investigated, and the impact of the parameter p on the optimal release time minimizing expected costs is assessed.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1149-1157
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• 2015

As a key part in the wind turbine system, the power electronic converter is proven to have high failure rates. At the same time, the failure of the wind power converter is becoming more unacceptable because of the quick growth in capacity, remote locations to reach, and strong impact to the power grid. As a result, the correct assessment of reliable performance for power electronics is a crucial and emerging need; the assessment is essential for design improvement, as well as for the extension of converter lifetime and reduction of energy cost. Unfortunately, there still exists a lack of suitable physic-of-failure based evaluation tools for a reliability assessment in power electronics. In this paper, an advanced tool structure which can acquire various reliability metrics of wind power converter is proposed. The tool is based on failure mechanisms in critical components of the system and mission profiles in wind turbines. Potential methodologies, challenges, and technology trends involved in this tool structure are also discussed. Finally, a simplified version of the tool is demonstrated on a wind power converter based on Double Fed Induction Generator system. With the proposed tool structure, more detailed information of reliability performances in a wind power converter can be obtained before the converter can actually fail in the field and many potential research topics can also be initiated.

• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.87-94
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• 2004

The software reliability growth model(SRGM) has been developed in order to estimate such reliability measures as remaining fault number, failure rate and reliability for the developing stage software. Almost of them assumed that the faults detected during testing were evetually removed. Namely, they have studied SRGM based on the assumption that the faults detected during testing were perfectly removed. The fault removing efficiency. however. IS imperfect and it is widely known as so in general. It is very difficult to remove detected fault perfectly because the fault detecting is not easy and new error may be introduced during debugging and correcting. Therefore, the fault detecting efficiency may influence the SRGM or cost of developing software. It is a very useful measure for the developing software. much helpful for the developer to evaluate the debugging efficiency, and, moreover, help to additional workloads necessary. Therefore. it is very important to evaluate the effect of imperfect dubugging in point of SRGM and cost. and may influence the optimal release time and operational budget. I extent and study the generally used reliability and cost models to the imperfect debugging range in this paper.

• Convergence Security Journal
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• v.7 no.1
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• pp.45-53
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the hyper-exponential distribution reliability model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method. For model determination and selection, explored goodness of fit (the error sum of squares). The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution (shape 0.1 & scale 1) of Minitab (version 14) statistical package.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.9-18
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• 2015

Software Reliability Growth Models (SRGMs) are useful for determining the software release date or additional testing efforts by using software failure data. It is not appropriate for a SRGM to apply to all software. And besides a large number of SRGMs have already been proposed to estimate software reliability measures. Therefore selection of an optimal SRGM for use in a particular case has been an important issue. The existing methods for selecting a SRGM use the entire collected failure data. However, initial failure data may not affect the future failure occurrence and, in some cases, it results in the distorted result when evaluating the future failure. In this paper, we suggest a method for selecting a SRGM based on the evaluation goodness-of-fit using partial data. Our approach uses partial data except for inordinately unstable failure data in the entire failure data. We will find a portion of data used to select a SRGM through the comparison between the entire failure data and the partial failure data excluded the initial failure data with respect to the predictive ability of future failures. To justify our approach this paper shows that the predictive ability of future failures using partial data is more accurate than using the entire failure data with the real collected failure data.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.273-277
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• 2010

This research was performed to examine changes in the timing of the growth of crops along with changes in temperatures due tochanges and to analyze the change of water-supply-reliability by adding an analysis of the change of agricultural water supply patterns in the basin area of Miryang dam in Korea. Had-CM3 model from U.K. was the tool adopted for the GCM model, a stochastic, daily-meteorology-generation-model called LARS-WG was alsoused for downscaling and for the climate change scenario (A1B) which represents Korea's circumstances best. First of all, to calculate changes in the timing of the growth of crops during this period, the theory of GDD was applied. Except for the period of transplanting and irrigation, there was no choice but to find the proper accumulated temperature by comparing actual temperature data and the supply pattern of agricultural use due to limited temperature data. As a result, proper temperatures were found for each period. $400^{\circ}C$ for the preparation period of a nursery bed, $704^{\circ}C$ for a nursery bed's period, $1,295^{\circ}C$ for the rice-transplanting period, $1,744^{\circ}C$ for starting irrigation, and $3,972^{\circ}C$ for finishing irrigation. To analyze future agricultural supply patter changes, the A1B scenario of Had-CM3 model was adopted, and then Downscaling was conducted adopting LARS-WG. To conduct a stochastical analysis of LARS-WG, climate scenarios were generated for the periods 2011~2030, 2046~2065, 2080~2099 using the data of precipitation andMax/Min temperatures collected from the Miryang gauging station. Upon reviewing the result of the analysis of accumulated temperatures from 2011~2030, the supply of agricultural water was 10 days earlier, and in the next periods-2046~2065, 2080~2099 it also was 10 days earlier. With these results, it is assumed that the supply of agricultural water should be about 1 month ahead of the existing schedule to meet the proper growth conditions of crops. From the results of the agricultural water supply patterns should be altered, but the reliability of water supply becomes more favorable, which is caused from the high precipitation change. Furthermore, since the unique characteristics of precipitation in Korea, which has high precipitation in the summer, water-supply-reliability has a pattern that the precipitation in September could significantly affect the chances of drought the following winter and spring. It could be more risky to make changes to the constant supply pattern under these conditions due to the high uncertainty of future precipitation. Although, several researches have been conducted concerning climate changes, in the field of water-industry, those researches have been solely dependent on precipitation. Even so, with the high uncertainty of precipitation, it is difficult for it to be reflected in government policy. Therefore, research in the field of water-supply-patterns or evapotranspiration according to the temperature or other diverse effects, which has higher reliability on anticipation, could obtain more reliable results in the future and that could result in water-resource maintenance to be safer and a more advantageous environment.

• Journal of the Microelectronics and Packaging Society
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• v.15 no.2
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• pp.47-54
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• 2008

In this paper, we studied how and why did abnormal IMC growth at component affect on board level mechanical reliability. First, interfacial reactions between Sn2.5Ag0.5Cu solder and electrolytic Ni/Au UBM of component side were investigated with reflow times and thermal aging time. Also, to compare mechanical reliability of component level, shear energy was evaluated using the ball shear test conducted with variation of shear tip speed. Finally, to evaluate mechanical reliability of board level, we surface-mounted component fabricated with each condition on PCB side. After conducting of 3 point bending test and impact test, we confirmed solder joint crack mode using cross-sectioning and dye & pry penetration method.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.389-398
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• 2002

Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process(NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with several model on the constant reflecting the quality of testing. The performance measures and parametric inferences of the suggested models using Rayleigh distribution and Laplace distribution are discussed. The results of the suggested models are applied to real software failure data and compared with Goel model. Tools of parameter point inference and 95% credible intereval was used method of Gibbs sampling. In this paper, model selection using the sum of the squared errors was employed. The numerical example by NTDS data was illustrated.

• Journal of Ocean Engineering and Technology
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• v.9 no.1
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• pp.83-91
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• 1995

Surface defects in structural members are apt to be origins of fatigue cracks growth, which may cause serious failure of whole structures. Most structure has a part where stress concentrates such as welded joints, corner parts, etc. And then, analysis on crack growth and penetration from these defects, therefore, is one of the most important subjects for the reliability of LBB design. The present paper has performed an experimental and analysis on the fatigue crack propagation by variety in crack length of surface cracked plate with stress concentration part. The crack growth behavior can be explained quantitatively by using Newman-Raju equation and the stress partitioning method proposed by ASME B&P Code Sec. XI. The stress concentration factor $K_t$ has affected on the crack growth. The crack growth after penetration depends upon the initial front side crack length.