• Journal of Korean Society of Industrial and Systems Engineering
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• v.11 no.18
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• pp.71-80
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• 1988

Process capability implies the qualitative capability of a process, and it is necessary to specify the process capability by quantification and to evaluate the level with the specified standardizaion. But the process capability index is currently used to evaluate the performance of quality control activity. without considering the characteristics of process structure or the economy of management. Here the researcher would like to redefine process capability and emphasize its index may be used as the measure of managerial assessment and the objective of process quality control in full consideration of the economic aspects of process characteristics. Too little or too much process capability causes a loss of or excess. The proper economic level of process capability varies to each process. The procedure of taking the optimum process capability index is derived from the expected profit function, whereas each method is studied in cases of normal process with one-sided specification and two-sided specification. In addition, the process capability index is presented as a method of quality assurance. And an example is exhibited on wrapping process of 'A' company. The results of this study are summarized at follows. First, though the norminalization of the process capability index is possible by the existing methods, the optimum process capability index can vary to the situation of each process. So, the optimum process capability index which is suggested in this dissertation should be used as the standard to assess process capability. Second, the process capability index can take its effect not just in indicating quality control or managerial records but also in the management of high qualify assurance.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.229-241
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• 2004

Process capability index is used to determine whether a production process is capable of producing items within a specified tolerance. The index $C_{pmk}$ is the third generation process capability index. This index is more powerful than two useful indices $C_p$ and $C_{pk}$. Whether a process distribution is clearly normal or nonnormal, there may be some questions as to which any process index is valid or should even be calculated. As far as we know, yet there is no result for statistical inference with process capability index $C_{pmk}$. However, asymptotic method and bootstrap could be studied for good statistical inference. In this paper, we propose various bootstrap confidence limits for our process capability Index $C_{pmk}$. First, we derive bootstrap asymptotic distribution of plug-in estimator $C_{pmk}$ of our capability index $C_{pmk}$. And then we construct various bootstrap confidence limits of our capability index $C_{pmk}$ for more useful process capability analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.109-115
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• 2013

Process Capability Index (PCI) is useful Statistical Process Control (SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. $C_p$ and $C_{pk}$ are traditional PCIs. These are only considers of process variation. These are not given information about the characteristic value does not match the target value of the process. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. $C_{pm}$ is considers both the process variation and the process deviation from target value. And $C_{pm}{^+}$ is considers economic loss for the process deviation from target value. In this paper development of new process capability index that is Taguchi's quadratic loss function by applying the expected loss. And check the correlation between existing traditional process capability index ($C_{pk}$) and new one. Finally, we propose the criteria for classification about developed process capability index.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.127-132
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• 2014

This study is concerned with process capability index in single process. We enumerated issues on the calculation of process capability index and described the effects of these issues. We explained the development process and the reason of the representative existing process capability indices. We investigated whether the indices agree with the concept of process capability and drew the problems from those results. In addition, we proposed alternative and direction to seize the process capability necessary to the field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.2
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• pp.1-10
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• 2002

Process capability indices are widely used in industries and quality assurance system. In past years, process capability analysis have been used to characterize process performance on the basis of univariate quality characteristics. However, in actual manufacturing industrial, statistical process control (SPC) often entails characterizing or assessing processes or products based on more than one engineering specification or quality characteristic. 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.

• International Journal of Quality Innovation
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• v.9 no.1
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• pp.41-54
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• 2008

The process capability indices have been widely used to measure process capability and performance. In this paper, we proposed a new process capability index which is based on an actual dollar loss by defects. The new index is similar to the Taguchi's loss function and fully incorporates the distribution of quality attribute in a process. The strength of the index is to apply itself to non-normal or asymmetric distributions. Numerical examples were presented to show superiority of the new index against $C_p$, $C_{pk}$, and $C_{pm}$ which are the most widely used process capability indices.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.11-25
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• 2006

It is necessary to deal with the process capability index carefully because it has been developed with certain assumptions. Companies make a decision on processes through the results obtained by using and treating data extracted from the processes. However if they have incorrect or wrong results, they cannot lead to proper outputs but also bring to loss of the competition in quality. Therefore, this study will show a method to analysis Cp (process capability ; CP) and an idea of mass-production on Pp (process performance ; PP) based on the Sigma Estimate which is one of the uncertainty in the process capability index and makes a lot of error. To apply this method, it is essential to understand and to analyze the processes exactly. Especially, it is required to establish the more accurate process capability index that can quickly and properly respond to changes on processes to recognize the small changes on the process which lies in specification in mass production system that the continual monitoring of quality managers is required.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.41-49
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• 2017

Process quality control, which prevents problems and risks that may occur in products and processes, has been recognized as an important issue, and SPC techniques have been used for this purpose. Process Capability Index (PCI) is useful Statistical Process Control (SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. $C_p$ and $C_{pk}$ are traditional PCIs. These traditional $C_p$ and $C_{pk}$ were used only as a measure of process capability, taking into account the quality variance or the bias of the process mean. These are not given information about the characteristic value does not match the target value of the process and this has the disadvantage that it is difficult to assess the economic losses that may arise in the enterprise. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. $C_{pm}$ is considers both the process variation and the process deviation from target value. And $C_{pm}{^+}$ is considers economic loss for the process deviation from target value. In this paper we developed an improved Expected Loss Capability Index using Reflected Normal Loss Function of Spring. This has the advantage that it is easy to realistically reflect the loss when the specification is asymmetric around the target value. And check the correlation between existing traditional process capability index ($C_{pk}$) and new one. Finally, we propose the criteria for classification about developed process capability index.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.114-119
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• 2011

Process capability indices (PCls) have been widely used in manufacturing industries to provide a quantitative measure of process potential and performance. The previous studies have measured only one location on each part in the case of single variate. To calculate the reliable process capability, a couple of measuring locations on each part are required. In this paper, we propose a new system process capability index $SC_{pm}$ (m) which is the minimum value of the location PCls.

• 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.