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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Quality and Reliabil...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Quality and Reliability Engineering International
Article . 2017 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Unbiased Weibull capabilities indices using multiple linear regression

Authors: Manuel R. Piña-Monarrez; Manuel Baro-Tijerina; Jesús F. Ortiz-Yañez;

Unbiased Weibull capabilities indices using multiple linear regression

Abstract

Although the recently proposed Weibull process capability indices (PCIs) actually measure the times that the standard deviation (σx) is within the tolerance specifications, because they not accurately estimate neither the log‐mean (μx) nor the σx values, then the actual PCIs are biased. This actually because μx and σx are both estimated without considering the effect that the sample size (n) has over their values. Hence, μx is subestimated and σx is overestimated. As a response to this issue, in this paper, μx and σx are estimated in function of n. In particular, the PCIs' efficiency is based on the following facts: (1) the derived n value is unique and it completely determines η, (2) the μx value completely determines the η value, and (3) the σx value completely determines the β value. Thus, now, since μx and σx are in function of n and they completely determine β and η, then the proposed PCIs are unbiased, and they completely represent the analyzed process also. Finally, a step by step numerical application is given.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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