Open AccessAdaptive intelligence system for a predictive process for the Industry 4.0 in Tobacco factory
Author(s) -
T Latinović,
C Barz,
Aurélian Vadéan,
G. Sikanjic,
Ljilja Sikman
Publication year - 2020
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 - 10.1088/1742-6596/1426/1/012019
Subject(s) - factory (object oriented programming) , expert system , production (economics) , computer science , process (computing) , manufacturing engineering , productivity , industry 4.0 , quality (philosophy) , intelligent decision support system , key (lock) , risk analysis (engineering) , industrial engineering , artificial intelligence , engineering , data mining , computer security , medicine , philosophy , epistemology , economics , macroeconomics , programming language , operating system
Speaking of the biggest innovations for the manufacturing industry of the day, we are talking about intelligent production systems with “self-aware”, “self-contemplative and” self-sustaining “capabilities. Building such an intelligent system that is adapted and predictable provides the aforementioned capabilities in production, processes and machines. The intelligent system is able to combine various technologies and techniques for mixing statistical data, data, and artificial intelligence methods. Cigarette production is selected because it is highly serial. In such production, the use of expert systems in quality management in this area is not sufficiently developed, and with direct management, it generates great savings. Mistakes and errors are inversely proportional to productivity. This paper deals with the application of an intelligent system that uses the key principle of lean production. We need to build an adaptive system for predictive error and reduce the machine’s failure time in the cigarette industry.