Published Jul 12, 2021



PLUMX
Almetrics
 
Dimensions
 

Google Scholar
 
Search GoogleScholar


Gouda M. Mohamed

Riham S. Hegazy

##plugins.themes.bootstrap3.article.details##

Abstract

This research article refers to the application of the evaluated measurement uncertainty for deciding the statement of conformity. It is a proposal to rethink about the classification of measuring devices, taking into account the calculations of uncertainty as a decision rule. It is also a base for complete compatibility and harmonization between ISO 17025:2017 and the other standards. To verify this proposal a case study on compression testing machine classification is used. This proposal aims to review classification criteria for these machines. Since the uncertainty value is equivalent to all parameters that may affect the performance of these machines, it is logical and accurate to use it as the basis for the classification. This approach may be employed for the upcoming version of ISO 7500 standard to use the uncertainty value as a base for machine classification.

Keywords

Conformity statement, confidence level, decision rule, uncertainty estimation

References
[1] JCGM. 100 Guide to the Expression of Uncertainty in Measurement (GUM), and its supplements,
Joint Committee on Guides in Metrology, 2008.
doi: https://www.bipm.org/documents/20126/2071204/JCGM_100_2008_E.pdf/cb0ef43fbaa5-11cf-3f85-4dcd86f77bd6.

[2] JCGM. 102 Evaluation of measurement data – Supplement 2 to the Guide to the expression of uncertainty in measuremen – Extension to any number of output quantities Joint Committee on Guides in Metrology, 2011.
doi: https://www.oiml.org/en/files/pdf_g/g001-102-e11.pdf

[3] Sniazhana S. Uncertainty in decision-making: A review of the international business literature, Cogent Business & Management, 6: 1-32,2019.
doi: 10.1080/23311975.2019.1650692

[4] Pendrill LR. Using measurement uncertainty in decision-making and conformity assessment,
Metrologia, 51(4): 1-14, 2014.
doi: 10.1088/0026-1394/51/4/S206

[5] Carlo C, Francesca P. Bayesian conformity assessment in presence of systematic measurement errors, Metrologia, 53(2): 9, 2016.
doi: 10.1088/0026-1394/53/2/S74

[6] Pravakar MA. Case Study on Decision Making with Expression of Uncertainty in Measurement, IEEE Region 10 Colloquium and the third ICIIS, Kharagpur, INDIA December 8-10, 2008.
doi: 10.1109/ICIINFS.2008.4798364

[7] Emilia M. Towards improving decision making and estimating the value of decisions in value-based software engineering, the value framework, Software Quality Journal, 26: 607–656, 2018.
doi: 10.1007/s11219-017-9360-z

[8] Ahmed A, Ebtisam H, Gouda M, Ahmadein M. The resolution uncertainty associated with digital indications revisited: the inclusion of the quantization effect and the impact of noise presence in the estimation process, Metrologia, 55:883–892, 2018.
doi: https://iopscience.iop.org/article/10.1088/1681-7575/aaebb6/meta

[9] ISO 7500-1. Fifth edition - Metallic materials — Calibration and verification of static uniaxial testing machines —Part 1: Tension/compression testing machines — Calibration and verification of the force-measuring system, 2018.
doi: https://www.iso.org/standard/72572.html.

[10] ISO/IEC 17025:2017. General requirements for the competence of testing and calibration laboratories.
doi: https://www.iso.org/standard/66912.html

[11] ILAC G8:09/2019. Guidelines on Decision Rules and Statements of Conformity.
doi: https://ilac.org/latest_ilac_news/revised-ilac-g8-published/

[12] Mahmoud G, Hegazy R. Comparison of GUM and Monte Carlo methods for the uncertainty estimation in hardness measurements, International Journal of Metrology and Quality Engineering, 8: 14-20, 2017.
doi: 10.1051/ijmqe/2017014
How to Cite
Mohamed, G. M., & Hegazy, R. S. . (2021). An investigation on using measurement uncertainty as decision rule for statement of conformity. Universitas Scientiarum, 26(2), 179–191. https://doi.org/10.11144/Javeriana.SC26-2.aiou
Section
Scientific and Industrial Metrology