Improvement of the quality management system of industrial enterprises based on the use of corporate knowledge

Abstract

This article analyzes the procedures for improving quality management using the example of solving problems of compliance with product quality requirements at industrial enterprises. The quality of the products largely depends on the use of modern methods and tools of quality management, as well as on improving the competence of personnel in the field of quality systems. In this regard, it is proposed to apply the corporate knowledge of the enterprise, including models and algorithms of artificial intelligence. Corporate knowledge is formed on the basis of the formation and processing of documentation, interviewing qualified specialists and intellectual data analysis on the implementation of business processes. During the research, an ontology of quality management was developed, decision-making rules were created and the results of improving the quality management system using a neuro-fuzzy network were predicted. The use of these artificial intelligence tools will make it possible to form a unified terminology to ensure an unambiguous perception of information by all participants in the process and the use of a knowledge base to support decision-making. It is proposed to use quality management tools to improve the efficiency of decisions made by intelligent tools, i.e. production rules and neural networks.