Preconditions of adapting simulation modeling based on the Takagi-Sugeno binary algorithm to improve the effectiveness of corporate quality management system

The article discusses the issue of assessing the effectiveness of corporate quality management system of a metallurgical company. Of parti­cular difficulty is the assessment of the effectiveness of corporate quality management systems (QMS) in large vertically integrated holdings, where classical approaches based on the achievement of established criteria often do not take into account industry specifics, multi-level structure and the impact of uncertainties. The object of the research is the vertically integrated corporate QMS of a large metallurgical holding company, which unites more than 10 production sites. The authors note that the traditional assessment methods used in the company do not fully take into account the residual risks of failure to achieve the target values of the performance criteria. As a solution, a modified methodology based on the Takagi–Sugeno algorithm is proposed, which integrates into the calculation not only the actual performance indicators of the processes and their weights, but also assessment of the residual risk for each criterion. The existing methodology for assessing the effectiveness of corporate QMS of a metallurgical company is compared with the proposed methodology, which implements the Takagi–Sugeno binary fuzzy set algorithm. Calculations for each method are implemented in a model based on the AnyLogic information system. Calculations using the developed model made it possible to assess the effectiveness of processes using both methods and to compare their applicability for performance assessments. Evaluating the effectiveness of corporate QMS for each method confirmed that the system is effective. Value of the effectiveness of the company’s QMS according to the existing methodology was 0.81, and according to the proposed one – 0.92. The use of the residual risk of process failure allows for a more accurate assessment of the effectiveness of corporate QMS. The developed model identified processes whose efficiency was overestimated or underestimated under the standard approach, which indicates the influence of risk factors.

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