@article{GrambowHieberOberhauseretal.2022,
  author    = {Gregor Grambow and Daniel Hieber and Roy Oberhauser and Camil Pogolski},
  title     = {ARPF - an Augmented Reality Process Framework for Context-Aware Process Execution in Industry 4.0 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-opus4-24698},
  pages     = {49 -- 59},
  year      = {2022},
  abstract  = {Although production processes in Industry 4.0 set- tings are highly automated, many complicated tasks, such as machine maintenance, continue to be executed by human workers. While smart factories can provide these workers with some digitalization support via Augmented Reality (AR) devices, these AR tasks depend on many contextual factors, such as live data feeds from machines in view, or current work safety conditions. Although currently feasible, these localized contextual factors are mostly not well-integrated into the global production process, which can result in various problems such as suboptimal task assignment, over-exposure of workers to hazards such as noise or heat, or delays in the production process. Current Business Process Management (BPM) Systems (BPMS) were not particularly designed to consider and integrate context-aware factors during planning and execution. This paper describes the AR-Process Framework (ARPF) for extending a BPMS to support context-integrated modeling and execution of processes with AR tasks in industrial use cases. Our realization shows how the ARPF can be easily integrated with prevalent BPMS. Our evaluation findings from a simulation scenario indicate that ARPF can improve Industry 4.0 processes with regard to AR task execution quality and cost savings.},
  language  = {en}
}