Open AccessDevelopment of intelligent algorithms for the continuous diagnostics and condition monitoring subsystem of the equipment as part of the process control system of a stainless steel pipe production enterprise
Author(s) -
Evgenii Grishin
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/939/1/012027
Subject(s) - process (computing) , production (economics) , computer science , software , quality (philosophy) , manufacturing engineering , manufacturing execution system , control (management) , systems engineering , process engineering , engineering , algorithm , computer integrated manufacturing , artificial intelligence , operating system , philosophy , epistemology , economics , macroeconomics
This article describes the process of development and implementation of an integrated APCS and continuous diagnostics and equipment condition monitoring subsystems using intelligent machine-learning-based algorithms for a stainless steel pipe manufacturing enterprise with combining local automatic control systems into a single information technology the system. Briefly, the author describes the technological equipment and the production cycle, its features, as well as its change as a result of the implementation of APCS. The software tools and their structure, the interaction of elements in the system, the main tasks solved with APCS and their impact on the quality of finished products are described. A feasibility study and justification of the application of PCS for this production are carried out.