Metrics Related to Confusion Matrix as Tools for Conformity Assessment Decisions

Author:

Božić Dubravka1ORCID,Runje Biserka1ORCID,Lisjak Dragutin2,Kolar Davor2ORCID

Affiliation:

1. Department of Quality, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia

2. Department of Industrial Engineering and Management, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia

Abstract

Conformity assessment refers to activities undertaken to check whether some product, service or process meets certain criteria and specifications given by internationally accepted standards. The decision on whether a property of interest is aligned with the set standards is made based on measurement. However, uncertainty associated with the measurement results may lead to incorrect decisions. Measurement results may be falsely rejected as non-conforming, although they meet specifications. This is referred to as the producer’s risk. If the measurement result that does not meet the required specifications is accepted as conforming, this is referred to as the consumer’s risk. This paper covers calculations of global consumer's and producer's risk using the Bayesian approach and deals with the application of metrics related to confusion matrices in conformity assessments. These techniques have been used to assess the conformity of the bearing ring diameter with the given specifications. Based on the behavior of these metrics, the optimal length of the guard band was determined with the aim of minimizing the global consumer’s and producer’s risk.

Funder

European Regional Development Fund

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference50 articles.

1. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP, and OIML (2023, March 26). Evaluation of Measurement Data—The Role of Measurement Uncertainty in Conformity Assessment, JCGM 106:2012. BIPM. Available online: https://www.bipm.org/documents/20126/2071204/JCGM_106_2012_E.pdf/fe9537d2-e7d7-e146-5abb-2649c3450b25?version=1.7&t=1659083025736&download=true.

2. Allard, A., Fischer, N., Smith, I., Harris, P., and Pendrill, L. (2019, January 24–26). Risk calculations for conformity assessment in practice. Proceedings of the 19th International Congress of Metrology, Paris, France.

3. Runje, B., Horvatić Novak, A., Razumić, A., Piljek, P., Štrbac, B., and Orošnjak, M. (2019, January 23–26). Evaluation of Consumer and Producer Risk in Conformity Assessment Decision. Proceedings of the 30th DAAAM International Symposium “Intelligent Manufacturing & Automation”, Zadar, Croatia.

4. (2023, May 18). ILAC-G8:09/2019. Guidelines on Decision Rules and Statements of Conformity. Available online: https://ilac.org/publications-and-resources/ilac-guidance-series/.

5. Puydarrieux, S., Pou, J.M., Leblond, L., Fischer, N., Allard, A., Feinberg, M., and El Guennouni, D. (2019, January 24–26). Role of measurement uncertainty in conformity assessment. Proceedings of the 19th International Congress of Metrology, Paris, France.

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