The application of neural network for provide functional stability of manufacturing processes

DOI:10.31673/2412-4338.2020.021328

Abstract

A large number of different publications in the field of functional stability of complex technical systems and in the field of artificial intelligence, namely neural networks, determines the need for analysis of results and their understanding in terms of assessing the feasibility of combining these areas. The characteristics of the behavior of complex technical systems that implement the property of functional stability of these systems are studied in the work. The article presents the definition of functionally stable production process of industrial enterprises and the criterion for ensuring its functional stability. Ensuring the functional stability of production processes is an important issue today. At present, many different methods have been proposed to ensure a high level of functional stability, but they need to be constantly changed and improved. Neural networks are a tool that allows you to create a deep hierarchy of decisions based on the location, type and level of the defect that occurred in the control system and, as a consequence, can be effectively used to solve this problem. Therefore, the article considers the features of the main provisions of the theory of artificial intelligence, namely neural networks, to ensure the functional stability of production processes of industrial enterprises. Based on the analysis, the article explores the possibilities of using neural networks to diagnose the state of systems and the practical application of neural network tools to detect and localize defects in systems, which is the key to ensuring the functional stability of production processes. The method of ensuring the properties of functional stability of the enterprise information system has been improved. Promising ways of further research in this area may be a wide range of issues related to the development of new and improvement of existing methods of ensuring the functional stability of production processes of enterprises, including means of artificial intelligence.

Keywords: neural network, manufacturing process, functional stability, multilayer feed forward network, radial basis network, Hopfield network, self-organizing neural network, activation function.

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