• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.18-34
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• 1999

This paper is a brief review of the different procedures that are available for fitting theoretical distributions to data. The use of each technique Is illustrated by reference to a distribution system which including the Pearson, Johnson and Burr functions. These functions can be used to calculate percent out of specification. Therefore, in this paper a new method for estimating a measure of process capability for Gamma distributed variable data proposed using the percentage nonconforming. Process capability indices combines with the percentage nonconforming Information can be used to evaluate more accurately process capability.

• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.437-448
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• 2007

This paper introduce information technology of software process assessment. It consists of eight parts such as concepts and introductory guide, a reference model for processes and process capability, performing an assessment, guide to performing assessments, an assessment model and indicator guidance, guide to competency of assessors, guide for use in process improvement, and guide for use in determining supplier process capability.

• Journal of Korean Society for Quality Management
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• v.45 no.2
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• pp.191-207
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• 2017

Purpose: To develop an interactive version of the conventional process capability-based approach, called 'Interactive Process Capability-Based Approach (IPCA)' in multi-response surface optimization to obtain a satisfactory compromise which incorporates a decision maker(DM)'s preference information precisely. Methods: The proposed IPCA consists of 4 steps. Step 1 is to obtain the estimated process capability indices and initialize the parameters. Step 2 is to maximize the overall process capability index. Step 3 is to evaluate the optimization results. If all the responses are satisfactory, the procedure stops with the most preferred compromise solution. Otherwise, it moves to Step 4. Step 4 is to adjust the preference parameters. The adjustment can be made in two modes: relaxation and tightening. The relaxation is to make the importance of one of the satisfactory responses lower, which is implemented by decreasing its weight. The tightening is to make the importance of one of the unsatisfactory responses higher, which is implemented by increasing its weight. Then, the procedure goes back to Step 2. If there is no response to be adjusted, it stops with the unsatisfactory compromise solution. Results: The proposed IPCA was illustrated through a multi-response surface problem, colloidal gas aphrons problem. The illustration shows that it can generate a satisfactory compromise through an interactive procedure which enables the DM to provide his or her preference information conveniently. Conclusion: The proposed IPCA has two major advantages. One is to obtain a satisfactory compromise which is faithful to the DM preference structure. The other is to make the DM's participation in the interactive procedure easier by using the process capability index in judging satisfaction/unsatisfaction. The process capability index is very familiar with quality practitioners as well as indicates the process performance levels numerically.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.81-100
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• 1999

Process capability indexes are widely used in industries. Nevertheless, important statistical issues that deal with the appropriate use of process capability indexes have only appeared in the technical literature and are thus unknown to many users. In this paper we will first review various kinds of process capability indexes and then try to understand how much uncertainty is associated with them in relation to the assumption of normal distribution, the estimate of ${\sigma}$, the sampling error, the size of number of observations available and the presence of data correlation. Finally, we will propose a proper use of process capability indexes in an effort to assess a complex process.

• 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,

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.69-79
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• 2004

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 multiple 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.

• Journal of Korean Society for Quality Management
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• v.26 no.4
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• pp.65-78
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• 1998

Process capability indices, used to determine whether a production process is capable of producing items within a specified tolerance, have been widely used in process assessments. In this paper, we consider some process capability indices using loss function when process is contaminated normal. Also, we examine some small sample properties related to these estimaters by some simulations.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.457-469
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• 2007

Process Capability Indexes(PCI) are used as the measure for evaluation of process capability analysis and is the statistical method for efficient process control. The fourth generation $PCI(C_{psk})$ is constructed from $C_{pmk}$ by introducing the factor $\mid\mu-T\mid$ in the numerator as an extra penalty for the departure of the process mean from the preassigned target value T And Process Incapability Indexes(PII) are presented by inversing PCI and include the information of PCI. This paper introduces the PII $C_{ss}^*$ provide manager with various information of process and include Gage R&R. PII $C_{ss}^*$ is presented by inversing PCI $C_{psk}$ and include the information of PCI $C_{psk}$.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.79-103
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• 2007

The main purpose of this study is to define antecedents that influence e-SCM synchronization and to investigate how it affects e-SCM performance. We, therefore, investigate (1) the impact of firms' internal IT planning capabilities on e-SCM synchronization and on SCM process management capability, (2) the impact of firms' internal IT infrastructure on e-SCM synchronization and on SCM process management capability, (3) the impact of firms' internal SCM process management capabilities on e-SCM synchronization, and finally (4) the impact of e-SCM synchronization on SCM performance. A survey has been administrated to the firms' SCM and marketing staffs and 171 returns analyzed. The results show that (1) IT plan has not direct impacts on e-SCM synchronization, but has direct impacts on organizational support, purchasing, and operations processes except logistics process. IT plan, however, has indirect impacts on e-SCM synchronization through purchasing and operations of SCM process management capability. (2) IT infrastructure has both direct and indirect effects on e-SCM synchronization, and also has direct impacts on organizational support, purchasing, and operations processes except logistics process. (3) SCM process management capabilities have direct impacts on e-SCM synchronization. Among these SCM core processes purchasing positively influences operations, which in turn positively influences logistics process management capability. (4) e-SCM synchronization has positive impacts on SCM performance indicator (SCOR), such as delivery reliability, responsiveness & flexibility, and cost. These results indicate that e-SCM synchronization can be critical to achieve better internal performance like cost and external performance like delivery reliability, responsiveness & flexibility of firms' SCM. In sum, this study demonstrates that the intervening role of e-SCM synchronization between e-SCM performance and IT management capability and between e-SCM performance and SCM core process management capability has been significant in achieving better e-SCM performance. Therefore, it can be suggested that e-SCM performance should be accomplished in consequence of the acceleration of e-SCM synchronization through the enhancement of preceding factors for the e-SCM synchronization.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.18-27
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• 2019

The process control methods based on the statistical analysis apply the analysis method or mathematical model under the assumption that the process characteristic is normally distributed. However, the distribution of data collected by the automatic measurement system in real time is often not followed by normal distribution. As the statistical analysis tools, the process capability index (PCI) has been used a lot as a measure of process capability analysis in the production site. However, PCI has been usually used without checking the normality test for the process data. Even though the normality assumption is violated, if the analysis method under the assumption of the normal distribution is performed, this will be an incorrect result and take a wrong action. When the normality assumption is violated, we can transform the non-normal data into the normal data by using an appropriate normal transformation method. There are various methods of the normal transformation. In this paper, we consider the Box-Cox transformation among them. Hence, the purpose of the study is to expand the analysis method for the multivariate process capability index using Box-Cox transformation. This study proposes the multivariate process capability index to be able to use according to both methodologies whether data is normally distributed or not. Through the computational examples, we compare and discuss the multivariate process capability index between before and after Box-Cox transformation when the process data is not normally distributed.