• Convergence Security Journal
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• v.7 no.2
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• pp.49-55
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• 2007

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. From the subdivision of this analysis, new attemp needs the side of the quality control. In this paper, we discuss process capability analysis using process capability indexs. Because of software failure interval time is pattern of nonnegative value, instead of capability analysis of suppose to normal distribution, capability analysis of process distribution using to Box-Cox transformation is attermpted. The used software failure time data for capability analysis of process is SS3, the result of analysis listed on this chapter 4 and 5. The practical use is presented.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.323-326
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• 2008

Data Envelopment Analysis (DEA) is a theoretically sound framework for performance analysis that offers many advantages over traditional methods such as performance ratios and regression analysis. Largely the result of multidisciplinary research during the last three decades in economics, engineering and management, DEA is best described as an effective new way of visualizing and analyzing performance data. Besides, overseas information technology companies have aggressively tried to enter the domestic market. In the age of globalization and high competition, it is imperative that the system integration (SI) companies need to introduce the performance evaluation models of SI projects, including Capability Maturity Model and Software Process Improvement and Capability Determination, to gain a competitive advantage. Therefore, it makes our research regarding evaluation of SI projects very opportune. The purpose of the study is not only to evaluate efficiency of each project by DEA but also to gain insight into various factors such as project complexity, team members' man-months structure, and process index(project management index) that link to the projects performance.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.451-464
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• 2008

Six sigma is the rating that signifies "best in clas", with only 3.4 defects per million units or operations. Higher sigma quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The process capability indices and the sigma level $Z_{st}$ have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider statistical inference for process capability indices $C_p$, $C_{pk}$ and $C_{pm}$. Also, we study better testing procedure on assessing sigma level $Z_{st}$ and capability index $C_{pm}$, for practitioners to use in determining whether a given process is capable. The proposed method is easy to use and the decision making is more reliable. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.151-157
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• 2019

This study is about the process capability index (PCI). In this study, we introduce several indices including the index $C_{PR}$ and present the characteristics of the $C_{PR}$ as well as its validity. The difference between the other indices and the $C_{PR}$ is the way we use to estimate the standard deviation. Calculating the index, most indices use sample standard deviation while the index $C_{PR}$ uses range R. The sample standard deviation is generally a better estimator than the range R. But in the case of the panel process, the $C_{PR}$ has more consistency than the other indices at the point of non-conforming ratio which is an important term in quality control. The reason why the $C_{PR}$ using the range has better consistency is explained by introducing the concept of 'flatness ratio'. At least one million cells are present in one panel, so we can't inspect all of them. In estimating the PCI, it is necessary to consider the inspection cost together with the consistency. Even though we want smaller sample size at the point of inspection cost, the small sample size makes the PCI unreliable. There is 'trade off' between the inspection cost and the accuracy of the PCI. Therefore, we should obtain as large a sample size as possible under the allowed inspection cost. In order for $C_{PR}$ to be used throughout the industry, it is necessary to analyze the characteristics of the $C_{PR}$. Because the $C_{PR}$ is a kind of index including subgroup concept, the analysis should be done at the point of sample size of the subgroup. We present numerical analysis results of $C_{PR}$ by the data from the random number generating method. In this study, we also show the difference between the $C_{PR}$ using the range and the $C_P$ which is a representative index using the sample standard deviation. Regression analysis was used for the numerical analysis of the sample data. In addition, residual analysis and equal variance analysis was also conducted.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.275-285
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• 1995

In recent years there has been increasing interest in the issue of process centering in manufacturing process, The traditional process capability indices Cp, Cpk and Cpu are used to provide measure of process performance, but these indices do not represent the issue of process centering. A new measure of the process capability index Cpm is proposed that takes into account the proximity to the target value as well as the process variation when assessing process performance. However, Cpm only considers acceptance cost for deviation from target value within specification limits, do not includes economic consideration for rejected items. This paper proposes flexible process performance measures that considered quadratic loss function caused by quality deviation within specification limits, rejection cost associated with the disposition of rejected items, and inspection cost. In this model disposition of rejected items are considered under perfect corrective procedures and the absence of perfect corrective procedures.

• Journal of Korean Society for Quality Management
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• v.41 no.2
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• pp.233-248
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• 2013

Purpose: This study develops heuristic process capability indices (PCIs) using distribution-decomposition methods and evaluates the performances. The heuristic methods decompose the variation of a quality characteristic into upper and lower deviations and adjust the value of the PCIs using decomposed deviations in accordance with the skewness. The weighted variance(WV), new WV(NWV), scaled WV(SWV), and weighted standard deviation(WSD) methods are considered. Methods: The performances of the heuristic PCIs are investigated under the varied situations such as various skewed distributions, sample sizes, and specifications. Results: WV PCI is the best under the normal populations, WSD and SWV PCIs are the best under the low skewed populations, NWV PCI is the best under the moderate and high skewed populations. Conclusion: Comprehensive analysis shows that the NWV method is most adequate for a practical use.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.8
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• pp.894-903
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• 2011

In this paper, the capability index is introduced in order to improve the reliability of new concept machine tools and the method to improve the machine accuracy from the analysis of cutting process, statistical methodology and influence factors are proposed. In addition, the rib structure of bed and column in machine tools is analyzed by using the thermal impact method in order to analogize the rib pattern which has the small thermal deformation under thermal boundary condition. In the analysis of column rib structure, thermal boundary condition is separated to heat conduction and heat transfer to appropriate real boundary condition. Finally, performance chart of bed and column rib structure is provided for designer to estimate each rib pattern and select rib structure appropriating to thermal condition.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1132-1138
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• 2009

The spring constants of primary suspensions for a railway vehicle are optimized by a robust design process, in which the response surface models(RSMs) of their dynamic responses are constructed via the design of experiment(DOE). The robust design process requires an intensive computation to evaluate exactly a probabilistic feasibility for the robustness of dynamic responses with their probabilistic variances for the railway vehicle. In order to overcome the computational process, the process capability index $C_{pk}$ is introduced which enables not only to show the mean value and the scattering of the product quality to a certain extent, but also to normalize the objective functions irrespective of various different dimensions. This robust design, consequently, becomes to optimize the $C_{pk}$ subjected to constraints, i.e. 2, satisfying six sigma. The proposed method shows not only an improvement of some $C_{pk}$ violating the constraints obtained by the conventional optimization, but also a significant decrease of the variance of the $C_{pk}$.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.697-709
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• 2001

In this paper we study two vector-valued process capability indices $C_{p}$=($C_{px}$, $C_{py}$ ) and C/aub pm/=( $C_{pmx}$, $C_{pmy}$) considering process capability indices $C_{p}$ and $C_{pm}$ . First, two asymptotic distributions of plug-in estimators $C_{p}$=($C_{px}$, $C_{py}$ ) and $C_{pm}$ =) $C_{pmx}$, $C_{pmy}$) are derived.. With the asymptotic distributions, we propose asymptotic confidence regions for our indices. Next, obtaining the asymptotic distributions of two bootstrap estimators $C_{p}$=($C_{px}$, $C_{py}$ )and $C_{pm}$ =( $C_{pmx}$, $C_{pmy}$) with our bootstrap algorithm, we will provide the consistency of our bootstrap for statistical inference. Also, with the consistency of our bootstrap, we propose bootstrap asymptotic confidence regions for our indices. (no abstract, see full-text)see full-text)e full-text)

• Journal of Distribution Science
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• v.17 no.4
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• pp.51-57
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• 2019

Purpose - This study aims to improve the distribution structure of the OLED market and develop cost-effective optimization techniques. Specifically, it is a study on the optimization of ferric chloride to improve the etch of SUS MASK for OLED. Research design, data, and methodology - Applying the optimal conditions of the experiment, the final confirmation was evaluated for improvement by the Process Capability Index (Cpk). It is possible to derive social performance such as improvement of precision of SUS MASK manufacturing, economic performance such as defect rate, reduction of waste generation and treatment cost, technological achievement such as SUS MASK production technology, improvement of profit structure of technology development and process improvement do. Results - The improvement of the Cpk before the improvement was made was confirmed to be 0.57% with a defect estimate of 25.07% with a failure estimate of 0.57% after the improvement, and 8.84% with a failure estimate of 0.57% level after the improvement. Conclusions - If the conclusions obtained from the specimen experiment are applied to the manufacturing process of SUS MASK, it will be possible to expect excellent cost-effective competitiveness due to the improvement of precision and reduction of defect rate to enhance the OLED market penetration.