This article has an erratum: [https://doi.org/10.1051/ijmqe/2021013]
Int. J. Metrol. Qual. Eng.
Volume 11, 2020
|Number of page(s)||21|
|Published online||11 December 2020|
Variable data measurement systems analysis: advances in gage bias and linearity referencing and acceptability
Texas Instruments Inc. Quality Standards and Statistical Services, Dallas, TX 75243, USA
* Corresponding author: email@example.com
1 Retired in 2017. Consultant
Accepted: 23 October 2020
Measurement systems analysis (MSA) is a set of requirements and procedures adopted by the automotive industry and other disciplines to evaluate the accuracy and precision of measurement systems through assessing and quantifying the random and systematic errors and assigning appropriate dispositions for tolerance and performance acceptance. The methodology of variable data MSA comprises studies of a system's stability, bias, linearity and gage repeatability and reproducibility (GR&R). This paper describes advances in referencing and criteria for estimation of uncertainty errors, dispositions, and acceptability of MSA bias and linearity, proposing an extension to the basic statistical zero null-hypothesis to include overlap between confidence intervals and uncertainty associated with the reference standards used in bias and linearity studies.
Key words: Measurement system / bias / linearity / traceable standard / consensus standard
© M. Abdelgadir et al., published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.