Model for Forming a Rational Structure of a Digital Quality Management System for a Machine-Building Enterprise

The article presents a mathematical model for forming a rational structure of a digital quality management system (QMS), taking into account organizational and functional risks, barriers, and effects of process digitalization, as well as the enterprise’s resource constraints. The relevance of the study is due to the fact that the full digitalization of all QMS processes in real conditions is rarely economically justified or organizationally achievable. Therefore, there is a need for a scientifically grounded approach that allows determining a rational structure of a digital QMS, ensuring a balance between the level of digitalization, risk management, and the system’s efficiency. A methodological approach based on the quantitative determination of the risk level and the level of digitalization of each QMS process is proposed. To account for the uncertainty of the initial data and the subjectivity of expert assessments, the model is based on a fuzzy inference system. This solution ensures the fl exibility and adaptability of the model, as well as its practical application in the context of uncertainty in expert assessments. The developed model forms the basis for the analytical selection of processes that require priority digitalization and the optimization of resource allocation within the enterprise. It allows you to determine the optimal level of digitalization for each process, ensuring that you achieve the desired results and efficiency at the lowest possible cost. The practical implementation of the model enables you to assess the impact of risks and digitalization on the sustainability of your entire quality management system, as well as to develop an adaptive strategy for its digital transformation.