Open AccessThe application of neural network for provide functional stability of manufacturing processes
Author(s) -
Andrii Sobchuk,
Ju. I. Olimpiyeva
Publication year - 2020
Publication title -
telekomunìkacìjnì ta ìnformacìjnì tehnologìï
Language(s) - English
Resource type - Journals
ISSN - 2412-4338
DOI - 10.31673/2412-4338.2020.021328
Subject(s) - stability (learning theory) , computer science , artificial neural network , hierarchy , field (mathematics) , production (economics) , artificial intelligence , process (computing) , property (philosophy) , complex system , risk analysis (engineering) , industrial engineering , machine learning , engineering , mathematics , business , philosophy , epistemology , economics , pure mathematics , market economy , macroeconomics , operating system
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.