EVALUATION OF THE ECONOMIC EFFECT OF IMPLEMENTING A FUZZY LOGICAL INDICATION SYSTEM FOR MAKING MANAGEMENT DECISIONS IN A TESTING LABORATORY

Abstract

The object of the study is the process of evaluating and economically substantiating the effect of implementing a fuzzy logical inference system into the process of making management decisions in a testing laboratory. The paper considers the current problem of increasing the efficiency of testing laboratory management in conditions of uncertainty, risk and limited statistical data, which is due to the need to ensure compliance with the requirements of international standards ISO/IEC 17025:2019, ISO 9001:2015 and ISO 31000:2018. It is noted that traditional probabilistic risk assessment methods do not always ensure the reliability of results in the event of insufficient data or the availability of qualitative expert assessments, while fuzzy logical inference systems allow for the effective combination of quantitative and linguistic risk parameters. The purpose of the study is to assess the economic effect of implementing a fuzzy logic-based management decision-making model in a testing laboratory, which allows minimizing losses, reducing uncertainty and increasing the effectiveness of management actions. The article presents a scientifically sound approach to quantitative assessment of the economic effect, which takes into account the reduction of costs for eliminating errors, reducing decision-making time, optimizing quality control processes and increasing the productivity of laboratory tests. The scientific novelty lies in the development of a methodology for determining the integral economic effect through a combination of risk reduction indicators obtained on the basis of a fuzzy model Q=f(I₁,I₂,…,I_n), with the economic parameters of laboratory functioning. A two-component evaluation system is proposed, which includes a direct effect - cost savings, and an indirect effect - an increase in personnel productivity and the efficiency of management processes.

The practical significance of the study is that the fuzzy logical inference system forms an adaptive management tool for laboratories, which allows making decisions based on a combination of quantitative indicators and expert judgments, taking into account measurement risks, the human factor and technological instability. The results obtained can be used to improve quality management systems in testing and metrology laboratories, as well as as a methodological basis for the development of digital intelligent risk management systems in the field of scientific and technical control.