Abstract
Measurement uncertainty is used to describe the quality of a measurement value and ensures the ability of a laboratory to reliably implement quality improvement initiatives. The repeatability and reproducibility (R&R) study is the program most widely used to assess measurement uncertainty. R&R study is based on the assumption of a normal probability distribution of measurement results. However, standard R&R methods are inadequate for evaluating measurement uncertainty in numerous situations involving an insufficiently realistic normality assumption. This study proposes a statistical model for determining the R&R variance for inter-laboratory measurement results. The Expectation Maximization (E-M) algorithm and generalized linear model (GLM) are applied to estimate the repeatability variance, and a developed method is designed for estimating inter-laboratory and reproducibility variance. The findings are employed to evaluate and improve measurement uncertainty in laboratory accreditation.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010 |
| Pages | 857-861 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2010 Dec 31 |
| Event | 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010 - Xiamen, China Duration: 2010 Oct 29 → 2010 Oct 31 |
Publication series
| Name | Proceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010 |
|---|
Other
| Other | 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010 |
|---|---|
| Country | China |
| City | Xiamen |
| Period | 10-10-29 → 10-10-31 |
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All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering
Cite this
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Estimation of repeatability and between-method reproducibility using a novel statistical model. / Chen, Ming Nan; Lyu, Jr Jung.
Proceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010. 2010. p. 857-861 5646487 (Proceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Estimation of repeatability and between-method reproducibility using a novel statistical model
AU - Chen, Ming Nan
AU - Lyu, Jr Jung
PY - 2010/12/31
Y1 - 2010/12/31
N2 - Measurement uncertainty is used to describe the quality of a measurement value and ensures the ability of a laboratory to reliably implement quality improvement initiatives. The repeatability and reproducibility (R&R) study is the program most widely used to assess measurement uncertainty. R&R study is based on the assumption of a normal probability distribution of measurement results. However, standard R&R methods are inadequate for evaluating measurement uncertainty in numerous situations involving an insufficiently realistic normality assumption. This study proposes a statistical model for determining the R&R variance for inter-laboratory measurement results. The Expectation Maximization (E-M) algorithm and generalized linear model (GLM) are applied to estimate the repeatability variance, and a developed method is designed for estimating inter-laboratory and reproducibility variance. The findings are employed to evaluate and improve measurement uncertainty in laboratory accreditation.
AB - Measurement uncertainty is used to describe the quality of a measurement value and ensures the ability of a laboratory to reliably implement quality improvement initiatives. The repeatability and reproducibility (R&R) study is the program most widely used to assess measurement uncertainty. R&R study is based on the assumption of a normal probability distribution of measurement results. However, standard R&R methods are inadequate for evaluating measurement uncertainty in numerous situations involving an insufficiently realistic normality assumption. This study proposes a statistical model for determining the R&R variance for inter-laboratory measurement results. The Expectation Maximization (E-M) algorithm and generalized linear model (GLM) are applied to estimate the repeatability variance, and a developed method is designed for estimating inter-laboratory and reproducibility variance. The findings are employed to evaluate and improve measurement uncertainty in laboratory accreditation.
UR - http://www.scopus.com/inward/record.url?scp=78650605560&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650605560&partnerID=8YFLogxK
U2 - 10.1109/ICIEEM.2010.5646487
DO - 10.1109/ICIEEM.2010.5646487
M3 - Conference contribution
AN - SCOPUS:78650605560
SN - 9781424464814
T3 - Proceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010
SP - 857
EP - 861
BT - Proceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010
ER -