• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.1
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• pp.111-116
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• 2009

Process capability indices have been widely used in manufacturing industries to provide a quantitative measure of process performance. PCIs have been developed to represent process capability more exactly. In the previous studies, only one designated location on each part has been measured. But multiple measurement locations on each part are required to calculate the reliable process capability. In this paper, we propose a new process capability index dealing the multiple measurement locations on each part. Also we showed the relationship between the new index and sigma level according to the number of measurement locations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.435-436
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• 2012

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.48-54
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• 2005

Recently, a couple of process capability indices are used to evaluate that the outputs of the process satisfy the specifications. An assumption of those indices is that the specifications of the characteristics are given single constant value. The display panel is a highly precise product and all the specifications of measure points are designed by their locations in the panel. So it is very difficult to locate the measurement facility to the exact position. In this paper, we propose a new process capability index in case of multi specifications and unfixable objects.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.48-60
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• 1998

This paper proposes a fourth generation index $C_{psk}$, constructed from $C_{psk}$, by introducing the factor｜$\mu$-T｜ in the numerator as an extra penalty for the departure of the process mean from the preassigned target value T. The motivation behind the introduction of $C_{psk}$ is that when $T\neqM$ process shifts away from target are evaluated without respect to direction. All indices that are now in use assume normally distributed data, and any use of the indices on non-normal data results in inaccurate capability measurements. In this paper, a new process capability index $C_{psk}$ is introduced for non-normal process. The Pearson curve and the Johnson curve are selected for capability index calculation and data modeling the normal-based index $C_{psk}$ is used as the model for non-normal process. A significant result of this research find that the ranking of the six indices, $C_{p}$, $C_{pk}$, $C_{pm}$, ${C^*}_{psk}$, $C_{pmk}$, $C_{psk}$in terms of sensitivity to departure of the process median from the target value from the most sensitive one up to the least sensitive are $C_{psk}$, $C_{pmk}$, ${C^*}_{psk}$,$C_{pm}$, $C_{pk}$, $C_{p}$.

• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.117-126
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• 2009

We develop methods for propagating and analyzing EPCI(Extended Process Capability Index) by using the error type that classifies into accuracy and precision. EPCI developed in this study can be applied to the three combined processes that consist of production, measurement and calibration. Little calibration work discusses while a great deal has been studied about SPC(Statistical Process Contol) and MSA(Measurement System Analysis). EPCI can be decomposed into three indexes such as PPCI(Production Process Capability Index), PPPI(Production Process Performance Index), MPCI(Measurement PCD, and CPCI(Calibration PCI). These indexs based on the type of error classification can be used with various statistical techniques and principles such as SPC control charts, ANOVA(Analysis of Variance), MSA Gage R&R, Additivity-of-Variance, and RSSM(Root Sum of Square Method). As the method proposed is simple, any engineer in charge of SPC. MSA and calibration can use efficientily in industries. Numerical examples are presentsed. We recommed that the indexes can be used in conjunction with evaluation criteria.

• Journal of Applied Reliability
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• v.13 no.3
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• pp.191-206
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• 2013

Application areas for Lifetime Performance Index(LPI), a kind of process capability index to be frequently used as a means of measuring process performance are illustrated with examples. Statistical properties for maximum likelihood and unbiased estimators of LPI are evaluated and discussed under Weibull distribution with known shape parameter. Furthermore, guidelines for selecting an estimator of LPI are also presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.233-240
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• 1998

Recently, Hong-Jun Kim et al. introduced an improved process incapability index $C^*_{psk}$ by the transformation of the $C_{psk}{\;}C^*_{psk}$. A simple transformation of $C_{psk}$, can be regard as a process incapability index, provides an uncontaminated separation between information concerning the process accuracy and precision while this kind of information separation is not available with the $C_{psk}$. By an identical conception, in this article a new process incapability index $C^*_{psk}$ for Non-Normal process can be proposed by the transformation of the process capability index $C^*_{psk}$. The motivation behind introduction of $C^*_{psk}$ is that process capability index $C^*_{psk}$ cannot give information of the process accuracy and precision. A significant result of this research that $C^*_{psk}$ for the case where the target value T is equal to the midpoint of the specification limits or not Is evaluated without respect to T. Accordingly, $C^*_({psk})$ will be propose a reasonable process incapability measure for Non-Normal process

• 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 $C_{psk}$.

• 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.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.594-609
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• 1998

In this dissertation, a new process capability index $C_{psk}$ is introduced for non-normal process. The Pearson curve and the Johnson curve are selected for capability index calculation and data modeling the normal-based index $C_{psk}$ is used as the model for non-normal process. A significant result of this research find that the ranking of the seven indices, $C_p,\;C_{pk},\;C_{pm},\;C^{\ast}_{pm},\;C_{pmk},\;C_s,\;C_{psk}$ in terms of sensitivity to departure of the process median from the target value T=M from the most sensitive one up to the least sensitive are $C_{psk},\;C_{s},\;C_{pmk},\;C^{\ast}_{pm},\;C_{pm},\;C_{pk},\;C_p$. i.e, By the criteria adopted for evaluation of PCI's $C_{psk}$ is the most sensitive to the departure of the process median from target and $C_p$ is least