Open AccessManagement of material recourse supply of automotive enterprises based on expert systems
Author(s) -
Polina A. Nechaeva
Publication year - 2021
Publication title -
vestnik rossijskogo universiteta družby narodov. seriâ èkonomika
Language(s) - English
Resource type - Journals
eISSN - 2408-8986
pISSN - 2313-2329
DOI - 10.22363/2313-2329-2021-29-2-348-358
Subject(s) - procurement , expert system , automotive industry , variety (cybernetics) , corporation , supplier relationship management , process (computing) , computer science , fuzzy logic , business , risk analysis (engineering) , supply chain management , supply chain , marketing , artificial intelligence , engineering , finance , operating system , aerospace engineering
The importance of managing the material recourse supply has become apparent in the modern economy as it largely determines the survival of a corporation and its success in the market, which is especially important in a crisis. The procurement has a particular impact on this process. The problem of subjectivity when choosing a supplier is increasing in modern condition, which forces companies to use new tools, such as artificial intelligence system to make management decisions. The article proposes an expert supplier management system as an integral part of the material recourse supply management system for automotive enterprises. The possibility of improving the efficiency of procurement system, in particular supplier management. Based on a fuzzy expert system is considered. The fuzzy knowledge used to build the expert system will allow the company's management to take into account the uncertainty when making decisions about choosing a particular supplier, as well as see a description of the supplier's criteria that cannot be quantified. The use of an expert system becomes especially relevant when difficulties arise in objective decision making and choosing from a variety of alternatives. As a result of the work of the expert system, the top management of the company will receive an objective decision on choosing a supplier.