Artificial Intelligence and Evolutionary Approaches in Particle Technology
Since the early 2010s, after decades of premature excitement and disillusionment, the field of artificial intelligence (AI) is experiencing exponential growth, with massive real-world applications and high adoption rates both in daily life and in industry. In particle technology, there are already m...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hosokawa Powder Technology Foundation
2023-07-01
|
| Series: | KONA Powder and Particle Journal |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/kona/41/0/41_2024011/_html/-char/en |
| _version_ | 1797290921545433088 |
|---|---|
| author | Christoph Thon Marvin Röhl Somayeh Hosseinhashemi Arno Kwade Carsten Schilde |
| author_facet | Christoph Thon Marvin Röhl Somayeh Hosseinhashemi Arno Kwade Carsten Schilde |
| author_sort | Christoph Thon |
| collection | DOAJ |
| description | Since the early 2010s, after decades of premature excitement and disillusionment, the field of artificial intelligence (AI) is experiencing exponential growth, with massive real-world applications and high adoption rates both in daily life and in industry. In particle technology, there are already many examples of successful AI applications, for predictive modeling, process control and optimization, fault recognition, even for mechanistic modeling. However, in comparison to its still untapped potential and to other industries, further expansion in adoption rates and, consequently, gains in productivity, efficiency, and cost reduction are still possible. This review article is intended to introduce AI and its application scenarios and provide an overview and examples of current use cases of different aspects and unit operations in particle technology, such as grinding, extrusion, synthesis, characterization, or scale-up. In addition, hybrid modeling approaches are presented with examples of the intelligent combination of different methods to reduce data requirements and achieve beneficial synergies. Finally, an outlook for future opportunities is given, depicting promising approaches, currently being in the conception or implementation phase. |
| first_indexed | 2024-03-07T19:29:16Z |
| format | Article |
| id | doaj.art-bc92ca248fa843bc946c65d2416bcb5d |
| institution | Directory Open Access Journal |
| issn | 0288-4534 2187-5537 |
| language | English |
| last_indexed | 2024-03-07T19:29:16Z |
| publishDate | 2023-07-01 |
| publisher | Hosokawa Powder Technology Foundation |
| record_format | Article |
| series | KONA Powder and Particle Journal |
| spelling | doaj.art-bc92ca248fa843bc946c65d2416bcb5d2024-02-29T09:01:04ZengHosokawa Powder Technology FoundationKONA Powder and Particle Journal0288-45342187-55372023-07-0141032510.14356/kona.2024011konaArtificial Intelligence and Evolutionary Approaches in Particle TechnologyChristoph Thon0Marvin Röhl1Somayeh Hosseinhashemi2Arno Kwade3https://orcid.org/0000-0002-6348-7309Carsten Schilde4Institute for Particle Technology (iPAT), Technische Universität Braunschweig, GermanyInstitute for Particle Technology (iPAT), Technische Universität Braunschweig, GermanyInstitute for Particle Technology (iPAT), Technische Universität Braunschweig, GermanyInstitute for Particle Technology (iPAT), Technische Universität Braunschweig, GermanyInstitute for Particle Technology (iPAT), Technische Universität Braunschweig, GermanySince the early 2010s, after decades of premature excitement and disillusionment, the field of artificial intelligence (AI) is experiencing exponential growth, with massive real-world applications and high adoption rates both in daily life and in industry. In particle technology, there are already many examples of successful AI applications, for predictive modeling, process control and optimization, fault recognition, even for mechanistic modeling. However, in comparison to its still untapped potential and to other industries, further expansion in adoption rates and, consequently, gains in productivity, efficiency, and cost reduction are still possible. This review article is intended to introduce AI and its application scenarios and provide an overview and examples of current use cases of different aspects and unit operations in particle technology, such as grinding, extrusion, synthesis, characterization, or scale-up. In addition, hybrid modeling approaches are presented with examples of the intelligent combination of different methods to reduce data requirements and achieve beneficial synergies. Finally, an outlook for future opportunities is given, depicting promising approaches, currently being in the conception or implementation phase.https://www.jstage.jst.go.jp/article/kona/41/0/41_2024011/_html/-char/enartificial intelligencegenetic algorithmspredictive modelinghybrid modelingparticle technology |
| spellingShingle | Christoph Thon Marvin Röhl Somayeh Hosseinhashemi Arno Kwade Carsten Schilde Artificial Intelligence and Evolutionary Approaches in Particle Technology KONA Powder and Particle Journal artificial intelligence genetic algorithms predictive modeling hybrid modeling particle technology |
| title | Artificial Intelligence and Evolutionary Approaches in Particle Technology |
| title_full | Artificial Intelligence and Evolutionary Approaches in Particle Technology |
| title_fullStr | Artificial Intelligence and Evolutionary Approaches in Particle Technology |
| title_full_unstemmed | Artificial Intelligence and Evolutionary Approaches in Particle Technology |
| title_short | Artificial Intelligence and Evolutionary Approaches in Particle Technology |
| title_sort | artificial intelligence and evolutionary approaches in particle technology |
| topic | artificial intelligence genetic algorithms predictive modeling hybrid modeling particle technology |
| url | https://www.jstage.jst.go.jp/article/kona/41/0/41_2024011/_html/-char/en |
| work_keys_str_mv | AT christophthon artificialintelligenceandevolutionaryapproachesinparticletechnology AT marvinrohl artificialintelligenceandevolutionaryapproachesinparticletechnology AT somayehhosseinhashemi artificialintelligenceandevolutionaryapproachesinparticletechnology AT arnokwade artificialintelligenceandevolutionaryapproachesinparticletechnology AT carstenschilde artificialintelligenceandevolutionaryapproachesinparticletechnology |