Data Acquisition for Quality Loss Function Modelling

Søren Nygaard Pedersen; Thomas J. Howard

doi:10.1016/j.procir.2016.02.032

Data Acquisition for Quality Loss Function Modelling

Søren Nygaard Pedersen
, Thomas J. Howard

Research output: Contribution to journal › Conference article › Research › peer-review

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Abstract

Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by the product function in focus, the quality output can be measured and quantified in a number of ways. In this article a structured approach for acquiring stakeholder satisfaction data for use in quality loss function modelling is introduced.

Original language	English
Journal	Procedia CIRP
Volume	43
Pages (from-to)	112-117
ISSN	2212-8271
DOIs	https://doi.org/10.1016/j.procir.2016.02.032
Publication status	Published - 2016
Event	14th CIRP Conference on Computer Aided Tolerancing - Gothenburg, Sweden Duration: 18 May 2016 → 20 May 2016 http://www.chalmers.se/en/conference/cat2016/Pages/default.aspx

Conference

Conference	14th CIRP Conference on Computer Aided Tolerancing
Country/Territory	Sweden
City	Gothenburg
Period	18/05/2016 → 20/05/2016
Internet address	http://www.chalmers.se/en/conference/cat2016/Pages/default.aspx

Bibliographical note

Procedia CIRP is an open access product

Keywords

Quality loss functions
Data acquisition
Modelling

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10.1016/j.procir.2016.02.032

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title = "Data Acquisition for Quality Loss Function Modelling",

abstract = "Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by the product function in focus, the quality output can be measured and quantified in a number of ways. In this article a structured approach for acquiring stakeholder satisfaction data for use in quality loss function modelling is introduced.",

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AU - Howard, Thomas J.

N1 - Procedia CIRP is an open access product

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N2 - Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by the product function in focus, the quality output can be measured and quantified in a number of ways. In this article a structured approach for acquiring stakeholder satisfaction data for use in quality loss function modelling is introduced.

AB - Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by the product function in focus, the quality output can be measured and quantified in a number of ways. In this article a structured approach for acquiring stakeholder satisfaction data for use in quality loss function modelling is introduced.

KW - Quality loss functions

KW - Data acquisition

KW - Modelling

U2 - 10.1016/j.procir.2016.02.032

DO - 10.1016/j.procir.2016.02.032

M3 - Conference article

SN - 2212-8271

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SP - 112

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JO - Procedia CIRP

JF - Procedia CIRP

T2 - 14th CIRP Conference on Computer Aided Tolerancing

Y2 - 18 May 2016 through 20 May 2016

ER -

Data Acquisition for Quality Loss Function Modelling

Abstract

Conference

Bibliographical note

Keywords

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