@article{GrambowHieberOberhauser2022,
  author    = {Gregor Grambow and Daniel Hieber and Roy Oberhauser},
  title     = {Utilizing Fuzzy Sets and Rule Engines for Intelligent Task Assignment in Industry 4.0 Production Processes},
  series   = {International Journal on Advances in Intelligent Systems},
  volume    = {15},
  number    = {1\&2},
  issn      = {1942-2679},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:944-opus4-24703},
  pages     = {35 -- 48},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}