Generate QR code
Open Access
Subscription Access
Silver coin chemical composition two-parameter control system: measuring instruments selection for mass fraction of components
https://doi.org/10.32446/0368-1025it.2024-11-62-68
Abstract
The article considers general requirements for quality control of precious metal products. It presents an algorithm for developing a quality control system for silver coins and features of its application in monitoring the chemical composition of coins with a silver content of 79.7% to 92.8% (the balance is copper). An algorithm has been developed for making decisions based on the two-parameter control results, including mathematical models for calculating the indicators of control reliability (the probability of types I and II errors). The calculation of the errors in measuring mass fractions of silver and copper (standard deviation) was performed with the required reliability (the probability of type I errors is 0.10). The article describes the dependence of the probability of type I errors on the error (standard deviation) of mass fraction of alloy components in silver coins measurement result, which can be used to justify the requirements for the indicators of measurement accuracy. Based on the criteria “Analyzed elements”, “Measurement range”, “Error”, X-ray fl uorescence spectrometers were proposed for use in the control system. The described algorithm for developing a controlsystem and its implementation in monitoring the chemical composition of silver coins will be useful to employees involved in precious metals and jewelry in specialized institutes and organizations in the manufacturing industry, banks, jewelry stores, pawnshops.
About the Authors
Svetlana A. Mitrofanova
Academy of Standardization, Metrology and Certification (educational)
Russian Federation
Russian Federation
Moscow.
Irina V. Muravyeva
National University of Science and Technology “MISIS”; D. I. Mendeleev Russian University of Chemical Technology
Russian Federation
Russian Federation
Moscow.
References
1. Danilevich S. B. Reliability of results of multi-parameter measurement control. Systems of Control, Communication and Security, (4), 171–179 (2015). (In Russ.) https://sccs.intelgr.com/archive/2015-04/11-Danilevich.pdf
2. Korovina O. A. Estimate of risk for the manufacturer and the customer when monitoring the errors of measuring devices at one or more points. Measurement Techniques, 61(5), 434–439 (2018). https://doi.org/10.1007/s11018-018-1448-8
3. Dalalah D., Hani D. B. A precision-to-tolerance ratio model for the assessment of measurements uncertainty. Precision Engineering, 44, 143–151 (2016). http://dx.doi.org/10.1016/j.precisioneng.2015.11.003
4. Zilberbrand G. E. Selection and application of indicators of reliability of control and test results. Competency, 105(4), 44–46 (2013). (In Russ.) https://elibrary.ru/qavolr
5. Khayrullin R. Z., Kornev A. S., Kostoglotov A. A., Lazarenko S. V. Mathematical simulation of decision error functions in tolerance control of the performance of measuring techniques. Measurement Techniques, 63(9), 680–685 (2020). https://doi.org/10.1007/s11018-021-01839-y
6. Rubichev N. A., Frumkin V. D. Reliability of the quality control tolerance. Izdatelstvo standartov, Moscow (1990). (In Russ.)
7. Bogomolova S. A., Lukashov Yu. E., Shvarts M. Z. Analysis of the reliability of measurement monitoring of the power output of photovoltaic modules. Measurement Techniques, 57(12), 1338–1344 (2015). https://doi.org/10.1007/s11018-015-0631-4
8. Bogomolova S. A. Research and development of techniques to improve the efficiency of the monitoring process for testing equipment state in the production of thin-fi lm solar modules. Candidate’s dissertation Technical Sciences, VNIIMS, Moscow (2016). (In Russ.)
9. Loganina V. I. Reliability of control and measurement error in tolerance quality control of building materials. Regional’naya arhitektura i stroitel’stvo, 44(3), 17–21 (2020). (In Russ.) https://elibrary.ru/znkkpy
10. Erusalimchik I. G., Filippov M. N., Murav’eva I. V. Corrosion damage to a silver coin “Sobol”. Protection of Metals, 41(2), 203-204 (2005). https://doi.org/10.1007/s11124-005-0029-9
11. Erusalimchik I. G., Filippov M. N., Murav’eva I. V. Corrosion resistance of Zambian silver coin from the “African wildlife” series. Protection of Metals, 42(3), 301–302 (2006). https://doi.org/10.1134/S0033173206030167
12. Erusalimchik I. G., Karpov Yu. A., Murav’eva I. V., Potapcbuk E.A. Examination of electrochemical detector application for identification of ferrous, non-ferrous metals and alloys. Industrial laboratory. Diagnostics of materials, 72(7), 8–12 (2006). (In Russ.) https://elibrary.ru/hvdhzb
13. Fishchenko Yu. Yu., Makavetskas A. R., Smailov B. B., Smailova A. B. The significance of modern complex technological mineralogy methods for solving problems of increasing the gross recoverable value. Ratsionalnoe osvoenie nedr, (5-6), 30–35 (2015). (In Russ.) https://elibrary.ru/ymbatn
Supplementary files
Review
For citations:
Mitrofanova S.A., Muravyeva I.V. Silver coin chemical composition two-parameter control system: measuring instruments selection for mass fraction of components. Izmeritel`naya Tekhnika. 2024;(11):62-68. (In Russ.) https://doi.org/10.32446/0368-1025it.2024-11-62-68
Views:
128
Email this article 