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Utilizing Fuzzy Sets and Rule Engines for Intelligent Task Assignment in Industry 4.0 Production Processes

  • Today’s Industry 4.0 Smart Factories involve complicated and highly automated processes. Nevertheless, certain crucial activities such as machine maintenance remain that require human involvement. For such activities, many factors have to be taken into account, like worker safety or worker qualification. This adds to the complexity of selection and assignment of optimal human resources to the processes and overall coordination. Contemporary Business Process Management (BPM) Systems only provide limited facilities regarding activity resource assignment. To overcome these, this contribution pro- poses a BPM-integrated approach that applies fuzzy sets and rule processing for activity assignment. Our findings suggest that our approach has the potential for improved work distribution and cost savings for Industry 4.0 production processes. Furthermore, the scalability of the approach provides efficient performance even with a large number of concurrent activity assignment requests and can be applied to complex production scenarios with minimal effort.

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Metadaten
Author:Gregor Grambow, Daniel Hieber, Roy OberhauserORCiD
URN:urn:nbn:de:bsz:944-opus4-24703
URL:http://www.iariajournals.org/intelligent_systems/tocv15n12.html
ISSN:1942-2679
Source Title (English):International Journal on Advances in Intelligent Systems
Document Type:Article
Language:English
Year of Completion:2022
Release Date:2023/02/27
Tag:Assignment Automation; Business Process Management Systems; Fuzzy Logic; Resource Allocation Algorithms; Rule Engines
Volume:15
Issue:1&2
Number of Pages:14
First Page:35
Last Page:48
Faculty:Elektronik und Informatik
DDC classes:000 Allgemeines, Informatik, Informationswissenschaft
Open Access:Open Access
Relevance:peer reviewed
Licence (German):License LogoUrheberrechtlich geschützt