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Article
Publication date: 21 August 2002

Jing Sun

Process capability indices as an important kind of indices are intended to provide single‐number assessments of the inherent process capability to meet specification…

Abstract

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(s) 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 Dp and Dpk 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 ciscussed.

Details

Asian Journal on Quality, vol. 3 no. 2
Type: Research Article
ISSN: 1598-2688

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Article
Publication date: 25 September 2009

P. Castagliola, P. Maravelakis, S. Psarakis and K. Vännman

The purpose of this paper is propose a methodology for monitoring industrial processes that cannot be stabilized, but are nevertheless capable.

Abstract

Purpose

The purpose of this paper is propose a methodology for monitoring industrial processes that cannot be stabilized, but are nevertheless capable.

Design/methodology/approach

The proposed procedure uses the CP(u,v) family of capability indices proposed by Vännman (including the indices CPK, CPM, CPMK) combined with one‐sided two‐out‐of‐three and three‐out‐of‐four run rules strategies.

Findings

This paper introduces a new strategy, where capability indices are monitored in place of the classical sample statistics like the mean, median, standard deviation or range.

Practical implications

When doing a capability analysis it is recommended to first check that the process is stable, e.g. by using control charts. However, there are occasions when a process cannot be stabilized, but is nevertheless capable. Then the classical control charts fail to efficiently monitor the process position and variability. The approach suggested in this paper overcomes this problem.

Originality/value

The experimental results presented in this paper demonstrate how the new proposed approach efficiently monitors capable processes by detecting decreases or increases of capability level.

Details

Journal of Quality in Maintenance Engineering, vol. 15 no. 4
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 17 April 2008

Seungwook Park

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…

Abstract

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 Cp, Cpk, and Cpm which are the most widely used process capability indices.

Details

Asian Journal on Quality, vol. 9 no. 1
Type: Research Article
ISSN: 1598-2688

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Book part
Publication date: 1 September 2021

Amitava Mitra

A majority of products for manufacturing or consumers have multiple characteristics that must meet the requirements of the customer. For example, a steel beam any have…

Abstract

A majority of products for manufacturing or consumers have multiple characteristics that must meet the requirements of the customer. For example, a steel beam any have dimensional tolerances on its length, width, or height and functional tolerances on its strength. The characteristics are influenced by different processes that create the product. For an individual characteristic, process capability measures exist that convey the degree to which the characteristic meets the specification requirements. Such measures may indicate the proportion of nonconforming product related to the particular characteristic, under some distributional assumptions of the characteristic. For products with multiple characteristics, the unit costs of rectification may be different, making the satisfaction of some characteristics meeting customer requirements more important than others. In this paper, an aggregate process capability performance measure is developed that considers the relative importance of the characteristic based on unit costs of nonconformance. Based on the aggregate measure, appropriate process capability measures for the individual measures are also derived. Bounds on the aggregate capability measures are also established.

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Article
Publication date: 21 September 2012

Jeh‐Nan Pan and Sheau‐Chiann Chen

The purpose of this paper is to explore the relationship between multivariate process capability indices and loss functions for both nominal‐the‐best and…

Abstract

Purpose

The purpose of this paper is to explore the relationship between multivariate process capability indices and loss functions for both nominal‐the‐best and smaller‐the‐better cases, so the likelihood and consequences resulting from the nonconforming of a manufacturing process or an environmental system can be evaluated simultaneously.

Design/methodology/approach

In this paper, the authors present a new approach of correlated risk assessment by linking the multiple process capability indices and loss functions, in which the multivariate process capability indices and multivariate loss functions describe the likelihood and consequences as a result of nonconformities in multivariate manufacturing or environmental system, respectively. Then, the associated relationship equations are developed using multivariate methods. Moreover, a step‐by‐step procedure is provided to facilitate the implementation of the correlated risk assessment.

Findings

Given the multivariate process capability indices, the authors show that the expected loss can be estimated by developed relationship equations and two numerical examples are also given, to demonstrate how the correlated manufacturing and environmental risks can be properly assessed by linking the multivariate process capability indices and multivariate loss function.

Practical implications

The risk information of likelihood and expected loss, classified in the four planning zones of a strategic planning matrix, provides practising managers and engineers with a decision‐making tool for prioritizing their quality improvement projects when conducting risk assessment for any multivariate process or environmental system.

Originality/value

Once the existing quality/environmental problems and their Key Performance Indicators are identified, one may conduct risk assessment by applying the relationship equations to evaluate the impact of correlated risk on manufacturing processes or multiple environmental emissions inside company; this can lead to the direction of continuous improvement for any industry.

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Article
Publication date: 31 December 2015

Jeh-Nan Pan, Chung-I Li and Wei-Chen Shih

In the past few years, several capability indices have been developed for evaluating the performance of multivariate manufacturing processes under the normality…

Abstract

Purpose

In the past few years, several capability indices have been developed for evaluating the performance of multivariate manufacturing processes under the normality assumption. However, this assumption may not be true in most practical situations. Thus, the purpose of this paper is to develop new capability indices for evaluating the performance of multivariate processes subject to non-normal distributions.

Design/methodology/approach

In this paper, the authors propose three non-normal multivariate process capability indices (MPCIs) RNMC p , RNMC pm and RNMC pu by relieving the normality assumption. Using the two normal MPCIs proposed by Pan and Lee, a weighted standard deviation method (WSD) is used to modify the NMC p and NMC pm indices for the-nominal-the-best case. Then the WSD method is applied to modify the multivariate ND index established by Niverthi and Dey for the-smaller-the-better case.

Findings

A simulation study compares the performance of the various multivariate indices. Simulation results show that the actual non-conforming rates can be correctly reflected by the proposed capability indices. The numerical example further demonstrates that the actual quality performance of a non-normal multivariate process can properly reflected by the proposed capability indices.

Practical implications

Process capability index is an important SPC tool for measuring the process performance. If the non-normal process data are mistreated as a normal one, it will result in an improper decision and thereby lead to an unnecessary quality loss. The new indices can provide practicing managers and engineers with a better decision-making tool for correctly measuring the performance for any multivariate process or environmental system.

Originality/value

Once the existing multivariate quality/environmental problems and their Key Performance Indicators are identified, one may apply the new capability indices to evaluate the performance of various multivariate processes subject to non-normal distributions.

Details

International Journal of Quality & Reliability Management, vol. 33 no. 1
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 1 June 1990

Leslie J. Porter

Assert that capability indices quantify process improvement in a simple way and, when used correctly, provide relevant benchmarks. Considers it important that managers…

Abstract

Assert that capability indices quantify process improvement in a simple way and, when used correctly, provide relevant benchmarks. Considers it important that managers fully understand the power and limitations of this quality tool. Asserts the process is on target when Cp and Cpk are equal. Contends that the observed differences are due to sampling error and that any capability index is simply an estimate of an unknown value. Concludes that the measurement of process capability and the assessment on internal and external suppliers performance using indices, is now widespread. Despite any problems, process capability indices are preferable to many other measures of process or supplier performance.

Details

The TQM Magazine, vol. 2 no. 6
Type: Research Article
ISSN: 0954-478X

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Article
Publication date: 1 December 1998

Lee‐Ing Tong and Jann‐Pygn Chen

When the process probability distribution is non‐normal or is unknown, the process mean and standard deviation may not properly describe the distribution’s shape…

Abstract

When the process probability distribution is non‐normal or is unknown, the process mean and standard deviation may not properly describe the distribution’s shape. Consequently, the traditional process capability indices (PCI) Cp, Cpk, Cpm and Cpmk cannot express the actual process capability. This paper presents a procedure to construct lower confidence limits for PCIs when the process distribution is unknown. First, the order statistics are utilized to find the estimators of Cp, Cpk, Cpm and Cpmk. Bootstrap simulation method is then utilized to construct the lower confidence limits of PCIs, thereby allowing the process’s capability to be evaluated. A numerical example demonstrates the effectiveness of the proposed procedure.

Details

International Journal of Quality & Reliability Management, vol. 15 no. 8/9
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 1 July 1992

Abdul Raouf and Zulfiqar Ali

The process capability indices are used to assess the ability of a process to meet the present specification limits. These indices provide an easily understood…

Abstract

The process capability indices are used to assess the ability of a process to meet the present specification limits. These indices provide an easily understood qualification of a process performance. A fixed value for an ongoing process capability index is generally used. Minimization of statistical process control costs can be achieved by selecting an optimal process capability index. Presents a procedure to find an optimal ongoing process capability index.

Details

International Journal of Quality & Reliability Management, vol. 9 no. 7
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 26 June 2009

Davood Shishebori and Ali Zeinal Hamadani

The aim of this paper is to consider the effect of gauge measurement capability on the multivariate process capability index (MCp).

Abstract

Purpose

The aim of this paper is to consider the effect of gauge measurement capability on the multivariate process capability index (MCp).

Design/methodology/approach

With respect to measurement capability, the paper investigates the statistical properties of the estimated MCp and considers the effect of gauge measurement capability on the lower confidence bound, hypothesis testing, critical value and power of testing for MCp at the mentioned state.

Findings

The results show that gauge measurement capabilities will notably change the results of estimating and testing the process capability index.

Originality/value

The research would help quality experts to determine whether their processes meet the required capability, and to make more reliable decisions.

Details

International Journal of Quality & Reliability Management, vol. 26 no. 6
Type: Research Article
ISSN: 0265-671X

Keywords

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