Open AccessImprovement of electronic design and technological documentation approval procedure quality by using the apparatus of artificial neural networks
Author(s) -
М. В. Иванов,
S A Afanasenkov,
Е. А. Скорнякова
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1889/2/022070
Subject(s) - documentation , business process reengineering , artificial neural network , quality (philosophy) , computer science , product (mathematics) , systems engineering , production (economics) , service (business) , manufacturing engineering , process management , engineering management , engineering , artificial intelligence , business , philosophy , epistemology , geometry , mathematics , marketing , lean manufacturing , economics , macroeconomics , programming language
The necessity of the product life cycle processes reengineering such as design and production stages in order to reduce feedback between design and technological departments and production departments within the framework of the tasks of the organization’s quality management service has been substantiated. Design and technological documentation approval processes are overviewed within the usage of single integrated automated system environment. The apparatus of artificial neural networks is applied to simulate processes and identify redundant elements. An optimized neural network model of approval processes for design and technological documentation is obtained.