Autonomous Processes in Particle Technology. Issue 3 (15th December 2021)

• Record Type: Journal Article
• Authors: Nirschl, Hermann; Winkler, Marvin; Sinn, Tabea; Menesklou, Philipp
• Is Part Of: Chemie Ingenieur Technik. Volume 94:Issue 3(2022)
• Page Start: 230
• Page End: 239
• Publication Date: 2021-12-15
• Subjects: Autonomous processes -- Machine learning -- Particle characterization -- Particle technology; Chemical engineering -- Patents -- Periodicals; Chemical engineering -- Periodicals; Chemical industry -- Periodicals; Chemistry, Technical -- Periodicals; 660.05
• DOI: 10.1002/cite.202100059
• Languages: English
• ISSNs: 0009-286X

Abstract

Abstract: Battery materials, pharmaceuticals, solar cells, coffee powder, 3D printed components, etc., all these products have in common that they are predominantly made of particles. Ensuring high product quality with optimal raw material and energy utilization is only possible with extensive and many years of experience in the operation of such processes. This unsatisfactory situation is due to the complexity of particulate products, which still hinders extensive automation and autonomous process control. The challenge is to couple the respective basic operations with characterization devices, process dynamics and modern control algorithms to form a closed loop for process control. As a result, some day it should be possible to set the desired property profiles of particulate products with the most energy‐ and raw material‐efficient operation possible with a "push of a button". Abstract : The extensive developments in modeling, characterization devices, computing and storage technology and data communication in recent years now enable extensive research and testing of methods for autonomous process control in particle technology.