Model for Ensuring the Reliability of Expert Quality Control of Products and Processes

The reliability of the results of sensory analysis depends on a number of factors that affect the objectivity of the tests carried out. Today, the credibility of subjective measurements is primarily achieved through standardization. However, the issue of the credibility of subjective measurements remains, furthermore, it moves to a new level. Special attention must be paid to subjective measures related to the measurement of sensations to ensure credibility of results. The dynamics of increasing credibility through factor standardization lags behind the dynamics of stakeholder demand for increasing the credibility of subjective measurements. The purpose of the paper is to consider subjective measurements from the point of view of the development of the theory of quantitative measurements and to substantiate a process model for measurement that ensures the meaningfulness of the results in relation to expert assessments that ensure the subjectivity of measurements when conducting sensory tests, the results of which form decisions on compliance or non-compliance. The object of research is expert assessment methods used in sensory measurements, specifically in the evaluation of participating experts. The research methods used in this work include system analysis of measurement theories, method of alternatives, and standardized methods of expert assessment. A model of quantitative measurements is proposed to ensure meaningful measurement results, based on an analysis of the evolution of measurement theories. The problem of ensuring the meaningfulness of subjective measurements is formulated, which manifests itself in the form of risks of making incorrect decisions about characteristics of food products and processes based on expert assessments that lack reliability. An algorithm for quantitative measurements has been defined and tested on a specific example of expert assessment, demonstrating the importance of the identified problem of ensuring the reliability of expert assessments.

1. State Standard ISO 6658-2016. Sensory analysis – Methodology – General guidance, IDT. Moscow, Standartinform Publ., 2016. 20 (in Russian).

2. State Standard ISO 5492–2014. Sensory Analysis. Vocabulary. Moscow, Standartinform Publ., 2015. 50 (in Russian).

3. Lovkis Z. V., Morgunova H. M., Shevchenko V. I., Davydova H. A. (2018) Sensory Analysis of Quality of Food Products. Requirements to Assessors. Food Industry: Science and Technology, 11 (1), 13–19 (in Russian).

4. State Standard ISO 8586–2015. Sensory Analysis. General Guidelines for the Selection, Training and Monitoring of Selected Assessors and Expert Sensory Assessors. Moscow, Standartinform Publ., 2015. 25 (in Russian).

5. Hubbard D. W. (2010) How to Measure Anything: Finding the Value of Intangibles in Business. 2rd ed. New York, John Wiley & Sons. 432. https://doi.org/10.1002/9781118983836.

6. Pfanzagl J. (1971) Theory of Measurement. New York, John Willey and Sons. 968. https://doi.org/10.1007/978-3-662-41488-0.

7. Luce R. D., Krumhansl C. L. (1988) Measurement, Scaling, and Psychophysics. Atkinson R. C. (ed.) [et al.]. Stevens' Handbook of Experimental Psychology. N.Y., John Wiley & Sons, 3–74.

8. Knorring V. G. (1980) Development of Representative Measurement Theory. Izmereniya, Kontrol', Avtomatizatsiya: Nauchno-Tekhnicheskii Sbornik Obzorov [Measurement, Control, Automatization: a Collection of Scientific and Technical Reviews]. Moscow, All-Union Scientific Research Institute of Information and Economics (INFORMPRIBOR), (11–12), 3–10 (in Russian).

9. Tolstova Y. N. (2018) Correlation of Theoretical and Empirical Knowledge when Using Mathematical Methods in Sociological Research. Sociological Studies, (12), 39–48. https://doi.org/10.31857/S013216250003164-3 (in Russian).

10. Gusev A. N, Utochkin I. S. (2011) Psychological Measurements. Theory. Method. Moscow, AspektPress Publ. 317 (in Russian).

11. Romanchak V. M. (2018) The Subjective Measurement of Probability. Informatics, 15 (2), 74–82 (in Russian).

12. State Standard 43.0.4–2009. Informational Ensuring of Equipment and Operational Activity. Information in the Technical Activity. General Principles. Moscow, Standartinform Publ., 2018. 20 (in Russian).

13. Corbetta P. (2003) Social Research: Theory, Methods and Techniques. New York, Sage. 336. https://doi.org/10.4135/9781849209922.

14. Barzilai J. (2005) Measurement and Preference Function Modelling. Transactions in Operational Research, 12 (2), 173–183. https://doi.org/10.1111/j.1475-3995.2005.00496.x.

15. Barzilai J. (2010) Preference Function Modelling: The Mathematical Foundations of Decision Theory. Ehrgott M., Figueira J.R., Greco S. (eds). Trends in Multiple Criteria Decision Analysis. New York, Springer, 57–86. https://doi.org/10.1007/978-1-4419-5904-1_3.

16. Krantz D. H., Luce R. D., Suppes P, Tversky A. (1971) Foundation of Measurement. Vol. 1. New York, Academic Press. 606.

17. Staddon J. E. (1978) Theory of Behavioral Power Functions. Psychological Review, 85, 305–320. https://doi.org/10.1037/0033-295x.85.4.305.

18. Bridgman P. W. (1951) The Logic of Modern Physics. New York, Macmillan Company. 228.

19. Stevens S. (1946) On the theory of Scales Measurement. Science, 103 (2684), 677–680. https://doi.org/10.1126/science.103.2684.677.

20. Stevens S. (1957) On the Psychophysical Law. Psychological Review, 64 (3), 153–181. https://doi.org/10.1037/h0046162.

21. Kolmogorov A. N. (2006) Contemporary Debates on the Nature of Mathematics. Problems of Informational Transmission, 42, 379–389. https://doi.org/10.1134/S0032946006040107.

22. Levin S. F. (2012) Philosofical Problems and Statistical Methods of Fundamental Methrology. Metafizika = Metaphysics, (3), 89–118 (in Russian).

23. Shishkin I. F. (2016) Measurements of Non-Physical Quantities. Journal of Physics: Conference Series, 772, 1–7. https://doi.org/10.1088/1742-6596/772/1/012029.

24. Michell J. (1997) Quantitative Science and the Definition of Measurement in Psychology. British Journal of Psychology, 88 (3), 355–383. https://doi.org/10.1111/j.2044-8295.1997.tb02641.x.

25. Fridman А. А. (1965) The World is Like Space and Time. Moscow, Nauka Publ. 110 (in Russian).

26. Romanchak V. M. (2017) Model of Rating of Non Physical Quantity. System Analysis and Applied Information Science, (4), 34–44 (in Russian). https://doi.org/10.21122/2309-4923-2017-4-39-44.

27. State Standard ISO 16000-30–2017. Indoor air. Part 30. Sensory testing of indoor air. Moscow, Standartinform Publ., 2018. 30 (in Russian).