Sustainable Smart Manufacturing in Industry 4.0: Real-Time Resource Planning, Process Monitoring, and Production Control

2019 ◽  
Vol 14 (3) ◽  
pp. 30 ◽  
2021 ◽  
Vol 128 ◽  
pp. 01016
Author(s):  
Luyciena Piunko ◽  
Elena Tolkacheva

The research is devoted to the modern development of digital transformation in the Russian economy, including in the Khabarovsk Territory; the difficulties of implementing the directions of the “Digital Economy”. In this study, an attempt is made to compare the strategic goals of the development of the “Digital Economy”, modern processes of digital transformation and such an important component of it as "Integration 4.0" related to the “industrial Internet”, digital production, intelligent components, including the collection of large amounts of data, cyberphysical systems, remote monitoring and maintenance. “Industry 4.0” accelerates production processes, increases its efficiency and the quality of manufactured goods, reduces the cost of delivery, tracks production chains, etc. Currently, the industry of Western countries uses Industry 4.0 standards at the production management level. In developed countries, such as Germany, South Korea, etc., they realize the importance of automation and computerization, which became the main tool of the third industrial revolution, and its tools for the transition to “Industry 4.0”. International standards are developed for industries that use computer algorithms to monitor and control physical things, such as equipment, robots and vehicles. Standards that work on the basis of the Industrial Internet of Things (IIoT) and cyber—physical systems — intelligent autonomous systems that define all components of the supply chain, transforming production processes into “smart” - from smart manufacturing and factories to smart warehouses and logistics. And, the same systems are associated with the previous stage of industrial production, such as enterprise resource planning (ERP). All this ensures a high level of transparency and control over the activities of the organization. At the present stage, there are excellent opportunities for the development of Industry 4.0 in Russia, but there are also difficulties, overcoming which are significant directions of the digitalization processes of the modern economy. The authors devoted their research to the analysis of such difficulties.


2019 ◽  
Vol 11 (5) ◽  
pp. 1490 ◽  
Author(s):  
Jonghyuk Kim ◽  
Hyunwoo Hwangbo

In this study, real-time preventive measures were formulated for a crusher process that is impossible to automate, due to the impossibility of installing sensors during the production of plastic films, and a real-time early warning system for semi-automated processes subsequently developed. First, the flow of a typical film process was ascertained. Second, a sustainable plan for real-time forecasting in a process that cannot be automated was developed using the semi-automation method flexible structure production control (FSPC). Third, statistical early selection of the process variables that are most probably responsible for failure was performed during data preprocessing. Then, a new, unified dataset was created using the link reordering method to transform the time sequence of the continuous process into one time zone. Fourth, a sustainable prediction algorithm was developed using the association rule method along with traditional statistical techniques, and verified using actual data. Finally, the overall developed logic was applied to new production process data to verify its prediction accuracy. The developed real-time early warning system for semi-automated processes contributes significantly to the smart manufacturing process both theoretically and practically.


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