Author 1:
Name & Surname: Bondarenko A. V.
Company: RIVS Science and Production Association (Saint-Petersburg, Russia)
Work Position: Head of Analytical Center (AC), Deputy General Director
Scientific Degree: Candidate of Engineering Sciences
Contacts: e-mail: A_Bondarenko@rivs.ru

Author 2:
Name & Surname: Karamyshev N. I.
Company: RIVS Science and Production Association (Saint-Petersburg, Russia)
Work Position: Head of Programming Subdivision
Contacts: e-mail: N_Karamyshev@rivs.ru

Author 3:
Name & Surname: Trushin A. A.
Company: RIVS Science and Production Association (Saint-Petersburg, Russia)
Work Position: Director of Automation Department
Scientific Degree: Candidate of Engineering Sciences
Contacts: e-mail: A_Trushin@rivs.ru

Author 4:
Name & Surname: Katsman Ya. M.
Company: IVS Joint Venture (Saint-Petersburg, Russia)
Work Position: Principal Engineer
Scientific Degree: Candidate of Engineering Sciences
Contacts: e-mail: Y_Katsman@rivs.ru

The article addresses the issues of using the calculated balance of metal in conformance evaluation of a technology process and the production procedures and in detection of work points where the requisite performance is violated. The balance of metal is calculated according to the standard OST 48-157-79, where the measured values are adjusted, given the redundant data, using the maximum likelihood method, which reduces effect of measurement error on the estimate of the qualitative and quantitative parameters of a process. The features of software implementation of the described procedure are presented. The authors discuss the use of the calculated balance of metal in the analysis of state of a dressing process and in the statistical process control based on Shewhart charts (SC). With the said control charts, the process variability is analyzed, statistical controllability is evaluated and the need of human intervention (personnel or management) is defined. The authors describe a case study of SC involvement in the automatic process control at a processing plant. The authors insist on importance of continuous analysis of processes and the relevant training of specialists and managers for the efficient application of SC. The mathematical apparatus developed for automation of decision-making on control actions is characterized. The developed algorithms and programs are included in the RIVS shareable data base and are available for solving other problems in the framework of the general concept of the process and control information accumulation and organization.

1. Balans metallov. Raschety na elektronno-vychislitelnoy mashine. Spravochnoe posobie (Balance of metals. Computer calculations. Tutorial). Moscow : Nedra, 1991. (in Russian).
2. OST 48-157-79 «Raschet tekhnologicheskogo balansa metallov na obogatitelnykh fabrikakh Ministerstva Tsvetnoy Metallurgii SSSR s primeneniem matematicheskikh metodov i elektronno-vychislitelnoy mashiny (Industry Standard 48-157-79 “Calculation of technological balance of metals at concentration plants of Ministry of Non-Ferrous Metallurgy of USSR, with application of mathematical methods and computer). Moscow, 1979. (in Russian).
3. Voevodin V. V., Petrina R. V. Kompleks algoritmov, osnovannykh na preobrazovaniyakh tipa Gaussa, v pakete lineynoy algebry v sbornike «Chislennyy analiz na FORTRANe» (Complex of algorithms, based on Gauss-type dust-in basic linear algebra software in the collection “FORTRAN numerical analysis”). Moscow : Publishing House of Moscow State University, 1973. Iss. 3.
4. Bondarenko A. V., Nikandrov I. S., Andreev D. S. Otsenka vozmozhnostey analiticheskogo kompleksa na osnove rentgenofluorestsentnogo energodispersionnogo spektrometra s detektorom SDD-tipa pri analize rud i produktov obogashcheniya (Assessment of possibilities of analytical complex on the basis of X-ray fluorescence energy-dispersion spectrometer with SDD-type detector in the time of analysis of ores and concentration products). Gornyi Zhurnal = Mining Journal. 2014. No. 11.
5. Donald J. Wheeler, David S. Chambers. Statisticheskoe upravlenie protsessami. Optimizatsiya biznesa s ispolzovaniem kontrolnykh kart Shukharta (Understanding Statistical Process Control). Translated from English. Moscow : Alpina Business Books, 2009.
6. GOST R 50779.42-99 (ISO 8258-91). Statisticheskie metody. Kontrolnye karty Shukharta (State Standard R 50779.42-99 (ISO 8258-91). Statistical. Shewhart charts). Moscow : Publishing House of Standards, 1999. (in Russian).
7. Lyubushchenko A. D., Cherkas O. A., Kharchenko G. N., Klishevich L. G., Shastitko T. S., Sapeshko V. V., Stromskiy A. S. Razrabotka i vnedrenie sistemy statisticheskikh metodov kontrolya i upravleniya tekhnologicheskimi protsessami i kachestvom vypuskaemoy produktsii na Respublikanskom unitarnom predpriyatii «Proizvodstvennoe obedinenie «Belaruskaliy» (Development and introduction of system of statistic methods of control and management of technological processes and quality of manufactured products at JSC “Belaruskali”). Nauchno-tekhnicheskiy byulleten. Prilozhenie «Neftekhimicheskiy kompleks» = Scientific-technical bulletin. Application “Oil-chemical complex”. 2010. No. 1 (4).
8. Zimin A. V., Trushin A. A., Bondarenko A. V. Vektor razvitiya sredstv i sistem avtomatizatsii dlya gorno-obogatitelnykh proizvodstv v Nauchno-Proizvodstvennom Obedinenii «RIVS» (Way of development of means and automation systems for mining-concentration productions in Scientific-Production Association “RIVS”). Gornyi Zhurnal = Mining Journal. 2014. No. 11.
9. Bondarenko A. V., Karamyshev N. I., Katsman Ya. M. Nelineynoe otsenivanie parametrov v inzhenernoy praktike Nauchno-Proizvodstvennom Obedinenii «RIVS» (Non-linear accounting of parameters in engineering practice of Scientific-Production Association “RIVS”). Gornyi Zhurnal=Mining Journal. 2011. No. 10. pр. 73–78.