QUANTIFYING AND PREDICTING RISKS IN THE ORE-STREAM MANAGEMENT SYSTEM

Abstract

The aim of the work is to improve the quality of the management process by quantifying and predicting management and decision-making risks in multi-parameter systems, using ore streams as an example. The key to the ore management system in the article is the control process. The control process appears to be a complex procedure with measurement procedures, comparison of the measured value with the norm and decision making. Under conditions of parametric uncertainty of control agents, control is accompanied by decision-making errors in the form of false and undetected rejects. In real conditions, probable errors are defined as risks of two types: work producer risk and work customer risk. To quantify these risks, probabilistic and simulation models have been developed to investigate the impact of statistical characteristics of control and simulation agents on control results. The validity and effectiveness of the modelling is tested with a computer experiment. The developed modelling approach is universal and can be used in various scientific and technical practical applications. The authors propose a new multi-approach methodology for quantitative assessment of decision-making risks in a multi-parameter control system.