Measuring process capability index C pm with fuzzy data

Measuring process capability index C pm with fuzzy data The process capability index C pm , which considers the process variance and departure of the process mean from the target value, is important in the manufacturing industry to measure process potential and performance. This paper extends its applications to calculate the process capability index $${\tilde {C}_{pm} }$$ of fuzzy numbers. In this paper, the α-cuts of fuzzy observations are first derived based on various values of α. The membership function of fuzzy process capability index $${\tilde {C}_{pm} }$$ is then constructed based on the α-cuts of fuzzy observations. An example is presented to demonstrate how the fuzzy process capability index $${\tilde {C}_{pm} }$$ is interpreted. When the quality characteristic cannot be precisely determined, the proposed method provides the most possible value and spread of fuzzy process capability index $${\tilde {C}_{pm} }$$ . With crisp data, the proposed method reduces to the classical method of process capability index C pm . http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Measuring process capability index C pm with fuzzy data

Loading next page...
 
/lp/springer_journal/measuring-process-capability-index-c-pm-with-fuzzy-data-SeuAv1FV24
Publisher
Springer Netherlands
Copyright
Copyright © 2008 by Springer Science+Business Media B.V.
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-008-9211-x
Publisher site
See Article on Publisher Site

Abstract

The process capability index C pm , which considers the process variance and departure of the process mean from the target value, is important in the manufacturing industry to measure process potential and performance. This paper extends its applications to calculate the process capability index $${\tilde {C}_{pm} }$$ of fuzzy numbers. In this paper, the α-cuts of fuzzy observations are first derived based on various values of α. The membership function of fuzzy process capability index $${\tilde {C}_{pm} }$$ is then constructed based on the α-cuts of fuzzy observations. An example is presented to demonstrate how the fuzzy process capability index $${\tilde {C}_{pm} }$$ is interpreted. When the quality characteristic cannot be precisely determined, the proposed method provides the most possible value and spread of fuzzy process capability index $${\tilde {C}_{pm} }$$ . With crisp data, the proposed method reduces to the classical method of process capability index C pm .

Journal

Quality & QuantitySpringer Journals

Published: Dec 13, 2008

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off