• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.90-102
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• 1996

Process incapability index which is intended to evaluate the process capability by measuring process incapability provides more detailed information by dividing information about the process mean and variance. But when the target value is not consistent with the center of specification, it is very difficult to evaluate the process capability accurately. Thus it is necessary to improve the existing process incapability index. The improved process incapability index can identify the variation of the process faster than other process capability indices when applied firstly, to the precision process which can be affected sensitively by the change of the process, secondly, to the ordinary process where cost difference from the change of process is noticeable. By using subindices such as inaccuracy index and imprecision index, it is easier for quality manager to find where the cause of the variation of process is, and to take necessary action in advance.

• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.209-219
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• 2014

Purpose: The purpose of this study is to develop the statistical test for process capability index $C_p$ based on mixture normal process. Methods: This study uses Bootstrap method to calculate the approximate P-value for various simulation conditions under mixture normal process. Results: This study indicates that our proposed method is effective way to test for process capability index $C_p$ based on mixture normal process. Conclusion: This study finds out that statistical test for process capability index $C_p$ based on mixture normal process is useful for real application.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.74-83
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• 2002

Process capability indices as an important kind of indices are intended to provide single-number assessments of the inherent process capability to meet specification limits on quality characteristic(5) of interest. In this paper the condition for the application of process capability indices is analyzed. On the basis of process capability indices, dynamic process capability indices as a new kind of indices to show the current process capability are discussed and the condition for the application of dynamic process capability indices is exhibited. Comparison between process capability index and dynamic process capability index and comparison between $D_p$ and $D_pk$ are made and the conclusions provide the approach for process control. According to the requirement of process capability indices provided by customer, quality control based on process capability indices dynamic process capability indices is discussed.

• Journal of the Korea Safety Management & Science
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• v.10 no.2
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• pp.195-203
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• 2008

The purpose of this study is to develop a guideline of process capability evaluation and to apply this guideline improving the quality of products, especially in the small and medium enterprises. In this study we deal in the concept of process capability evaluation, the calculation of process capability index, and the application of a case study. Man must compare the state of process with the standards in evaluating of the process capability. Control chart can be used as a yardstick for judgement for the long term period and the distribution shape of histogram for the short term period. Man should regard to the significant figure by the calculation of process capability index.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.78-85
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• 2019

High variance observed in the measurement system can cause high process variation that can affect process capability badly. Therefore, measurement system analysis is closely related to process capability analysis. Generally, the evaluation for measurement system and process variance is performed separately in the industry. That is, the measurement system analysis is implemented before process monitoring, process capability and process performance analysis even though these analyses are closely related. This paper presents the effective concurrent evaluation procedure for measurement system analysis and process capability analysis using the table that contains Process Performance (Pp), Gage Repeatability & Reproducibility (%R&R) and Number of Distinct Categories (NDC). Furthermore, the long-term process capability index (Pp), which takes into account both gage variance and process variance, is used instead of the short-term process capability (Cp) considering only process variance. The long-term capability index can reflect well the relationship between the measurement system and process capability. The quality measurement and improvement guidelines by region scale are also described in detail. In conclusion, this research proposes the procedure that can execute the measurement system analysis and process capability analysis at the same time. The proposed procedure can contribute to reduction of the measurement staff's effort and to improvement of accurate evaluation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.116-123
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• 2005

The traditional process capability indices Cp, Cpk, Cpm, $Cpm^+$ have been used to characterize process performance on the basis of univariate quality characteristics. Cp, Cpk consider the process variation, Cpm considers both the process variation and the process deviation from target and Cpm+ considers economic loss for the process deviation from target. In manufacturing industry, there is growing interest in quantitative measures of process variation under multivariate duality characteristics. The multivariate process capability index incorporates both the process variation and the process deviation from target or considers expected loss caused by the process deviation from target. This paper proposes multivariate capability index based on the expected loss derived from multivariate normal distribution.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.375-384
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• 2000

The main objective of this paper to purpose a evaluating methods of process capability measures for exponential distributed quality characteristics. For correctly evaluating process capability , the first thing , exponential data is applied the Lilliefors test statistic to the null hypothesis of nornality. The next, exponential parameters is estimated in terms of MLE , ME , MME and then evaluated , respectively , process capability index based on exponential curved (Ιe) proposed by in this study and process capability indices based on Pearson system and Johnson system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.91-97
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• 2016

This study is concerned about the process capability index in single process. Previous process capability indices have been developed for the consistency with the nonconforming rate due to the process target value and skewness. These indices calculate the process capability by measuring one spot in an item. But the only one datum in an item reduces the representativeness of the item. In addition to the lack of representativeness, there are many cases that the uniformity of the item such as flatness of panel is absolutely important. In these cases, we have to measure several spots in an item. Also the nonconforming judgment to an item is mainly due to the range not due to the standard variation or the shift from the specifications. To imply the uniformity concept to the process capability index, we should consider only the variation in an item. It is the within subgroup variation. When the universe is composed of several subgroups, the sample standard deviation is the sum of the within subgroup variation and the between subgroup variation. So the range R which represents only the within subgroup variation is the much better measure than that of the sample standard deviation. In general, a subgroup contains a couple of individual items. But in our cases, a subgroup is an item and R is the difference between the maximum and the minimum among the measured data in an item. Even though our object is a single process index, causing by the subgroups, its analytic structure looks like a system process capability index. In this paper we propose a new process capability index considering the representativeness and uniformity.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.66-72
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• 2006

The process capability indices are widely used to measure the capability of the process to manufacture items within the specified tolerance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. The index $C_p$ has been widely used in various industries to assess process performance. In this paper, we propose new testing procedure on assessing $C_p$ index for practitioners to use in determining whether a given process is capable. The provided approach 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 the proposed approach is illustrated.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.503-521
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• 2005

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for muliple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index $MC_{pm}^{++}$ using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other,