Process capability plots—a quality improvement tool

Deleryd, Mats; Vännman, Kerstin

doi:10.1002/(sici)1099-1638(199905/06)15:3<213::aid-qre245>3.0.co;2-o

Cited by 65 publications

(16 citation statements)

References 14 publications

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“…This is an extension of the process capability plots for two-sided specification intervals discussed by Deleryd and Vännman [8] and Vännman [26]. This graphical method can also be extended to skewed, zero-bound distributions, as indicated in Section 3.…”

Section: Downloaded By [Northeastern University] At 12:24 04 Novembermentioning

confidence: 94%

Skewed zero-bound distributions and process capability indices for upper specifications

Albing

Vännman

2008

Journal of Applied Statistics

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A common practical situation in process capability analysis, which is not well developed theoretically, is when the quality characteristic of interest has a skewed distribution with a long tail towards relatively large values and an upper specification limit only exists. In such situations, it is not uncommon that the smallest possible value of the characteristic is 0 and this is also the best value to obtain. Hence a target value 0 is assumed to exist. We investigate a new class of process capability indices for this situation. Two estimators of the proposed index are studied and the asymptotic distributions of these estimators are derived. Furthermore, we suggest a decision procedure useful when drawing conclusions about the capability at a given significance level, based on the estimated indices and their asymptotic distributions. A simulation study is also performed, assuming that the quality characteristic is Weibull-distributed, to investigate the true significance level when the sample size is finite.capability index, skewed distributions, one-sided specification interval, upper specification limit, zero-bound process data, target value 0, hypothesis testing, Weibull distribution,

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Section: Downloaded By [Northeastern University] At 12:24 04 Novembermentioning

confidence: 94%

Skewed zero-bound distributions and process capability indices for upper specifications

Albing

Vännman

2008

Journal of Applied Statistics

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“…Chen (1997-1998) proposed a modification to MPPAC combining the more-advanced process capability index, C pm and C pmk , to identify the problems causing the processes failing to centre around the target. Deleryd and Va¨nnman (1999) provided a general framework using C dp (measuring relative process variation) and C dr (measuring relative process departure), which can be applied with appropriate modifications to develop various types of MPPAC charts using different indices, such as C pk , C pm , S pk , and C pmk . Chen et al (2001) extended the MPPAC for controlling product reliability with multiple characteristics where the manufacturing tolerances could be symmetric or asymmetric.…”

Section: The Index C Pmk and Capability Requirementmentioning

confidence: 99%

Monitoring manufacturing quality for multiple Li-BPIC processes based on capability indexC_pmk

Pearn

Shu

Hsu

2005

International Journal of Production Research

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The multi-process performance analysis chart (MPPAC) based on process capability indices has been developed to analyse the manufacturing performance for multiple processes, which conveys critical information regarding the departure of the process mean from the target value, process variability, capability levels, which provides a guideline of directions for capability improvement. Existing MPPAC researches have plotted the sample estimates of the process indices on the chart. Conclusions were then made on whether processes meet the capability requirement and directions need to be taken for further quality improvement. Such an approach is highly unreliable since the sample point estimate is a random variable with no assessment of the sampling errors. Further, existing MPPAC researches only considered one single sample. Current quality control practice is to estimate process capability using multiple groups of control chart samples rather than one single sample. In this paper, we propose the C pmk MPPAC combining the accuracy index C a to access the performance of multiple manufacturing processes. Distributions of the estimated C pmk and C a are derived based on multiple control chart samples, and accurate lower confidence bounds are calculated. The lower confidence bounds of the estimated C pmk and C a are then employed to the MPPAC to provide reliable capability grouping for those multiple processes. A real-world example is presented to illustrate the applicability of the proposed MPPAC.

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“…For efficient capability control and analysis, some recent research suggested various graphical methods to guide the directions for process improvement [12]. One of those graphical methods is called process capability plot, which conveys critical information regarding process spread and process centering.…”

Section: Manufacturing Capability Calculations and Controlmentioning

confidence: 99%

“…One of those graphical methods is called process capability plot, which conveys critical information regarding process spread and process centering. Process capability plots have been proposed and discussed by Gabel [13], Boyles [11,14], and Deleryd and Vannman [12]. Gable [13] refers to a process capability plot as the process performance chart, which is simply a plot of the spread of a process versus its mean.…”

Section: Manufacturing Capability Calculations and Controlmentioning

confidence: 99%

Measuring manufacturing capability for couplers and wavelength division multiplexers

Pearn

2004

Int J Adv Manuf Technol

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The couplers and wavelength division multiplexers have been widely used in high-speed, high-volume image data transmission systems to provide sufficient bandwidth and smaller channel spacing for greater throughput. In this paper, we develop a method for measuring the manufacturing capability of a process making couplers and wavelength division multiplexers. The proposed method measures the process capability of reproducing product items meeting the manufacturing specifications where multiple product quality characteristics are involved, including the polarization dependent loss, and the insertion loss, which are critical in fiber-optic transmission quality.

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Process capability plots—a quality improvement tool

Cited by 65 publications

References 14 publications

Skewed zero-bound distributions and process capability indices for upper specifications

Skewed zero-bound distributions and process capability indices for upper specifications

Monitoring manufacturing quality for multiple Li-BPIC processes based on capability indexC_pmk

Measuring manufacturing capability for couplers and wavelength division multiplexers

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Process capability plots—a quality improvement tool

Cited by 65 publications

References 14 publications

Skewed zero-bound distributions and process capability indices for upper specifications

Skewed zero-bound distributions and process capability indices for upper specifications

Monitoring manufacturing quality for multiple Li-BPIC processes based on capability indexCpmk

Measuring manufacturing capability for couplers and wavelength division multiplexers

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Product

Resources

About

Monitoring manufacturing quality for multiple Li-BPIC processes based on capability indexC_pmk