IMPROVING THE ENTERPRISE PERFORMANCE ON THE BASIS OF APPLYING DECISION TREE METHOD
Abstract and keywords
Abstract (English):
The article is devoted to considering the use of the decision tree method, defects at a machine-building enterprise, the reasons for having defects in the product and proposals for amending the normative and technical documentation. At the moment, non-destructive diagnostics methods have become widespread, which make it possible to determine the places of fault localization and predict the object state without the need for research which requires making object inoperative or its dismantling. The construction of the diagnostic models is implemented using the methods and tools of regression analysis, the theory of artificial neural networks, etc. However, they do not have a high level of generalization, and neural networks are difficult to interpret, which complicates their application in practice.

Keywords:
automation, automated systems, quality management, decision tree, efficiency
Text
Publication text (PDF): Read Download
References

1. Gofman, E.A. Using Decision Trees for Diagnosing Vehicles / E.A. Gofman, A.A. Oleinik, S.A. Subbotin - Text: electronic // ALGORITHMS, EXPERT SYSTEMS. - Available at: https://www.researchgate.net/publication/247158371_Ispolzovanie_derevev_resenij_dla_diagnostirovania_avtotransportnyh_sredstv/. - Date of publication: 01 January 2011

2. Progressive Technologies for Modeling, Optimization and Intelligent Automation of the Life Cycle Stages of Aircraft Engines: Monograph / A.V. Boguslaev, Al.A. Oleinik, An.A. Oleinik, D.V. Pavlenko, S.A. Subbotin. - Zaporozhye: OJSC “Motor Sich”, 2009. - 468 p. - ISBN 966-2906-19-3

3. GOST R 7.0.97-2016. Unified documentation system. Collection, Processing of Information. The Order of Procedure: approved and entered into force by the Order of the Federal Agency for Technical Regulation and Metrology of December 8, 2016 N 2004-st: nat. Russian Federation Standard: introduced for the first time: date of entry into force 01 July 2018 / prepared by the Federal budgetary institution “All-Russian Scientific Research Institute of Documentation and Archival Affairs” (ASRIDAA) of the Federal Archival Agency. - M.: Standartinform, 2019.

4. Chernysheva, T.Yu. Software Module for Project Risk Assessment Based on the Decision Tree / T.Yu. Chernysheva, A.G. Zhukov // Polzunovsky Bulletin. - 2012. - no. 3/2. - pp. 70-73

5. Bondarchuk, N.D. Increasing the Competitiveness of the Enterprise with the Help of Modern Management Methods / N.D. Bondarchuk, A.N. Feofanov, E.Yu. Bondarchuk, T.G. Grishina // Bulletin of Modern Technologies. - 2017. - no. 2 (6). - pp. 9-15.

6. Kuznetsova, N.V. Quality Management: tutorial / N.V. Kuznetsova. - M.: Flinta; MPSI. - 2009. - 360 p. - ISBN: 978-5-9770-0377-3

Login or Create
* Forgot password?