@inproceedings{GrambowHieberOberhauseretal.2021, author = {Gregor Grambow and Daniel Hieber and Roy Oberhauser and Camil Pogolski}, title = {Supporting Augmented Reality Industry 4.0 Processes with Context-aware Processing and Situational Knowledge}, series = {Proceedings of the Thirteenth International Conference on Information, Process, and Knowledge Management}, publisher = {IARIA XPS Press}, isbn = {978-1-61208-874-7}, issn = {2308-4375}, url = {https://nbn-resolving.org/urn:nbn:de:bsz:944-opus4-12860}, pages = {29 -- 36}, year = {2021}, abstract = {Production processes in Industry 4.0 settings are usually highly automated. However, many complicated tasks, such as machine maintenance, must be executed by human workers. In current smart factories, such tasks can be supported by Augmented Reality (AR) devices. These AR tasks rely on high numbers of contextual factors like live data from machines or work safety conditions and are mostly not well integrated into the global production process. This can lead to various problems like suboptimal task assignment, over-exposure of workers to hazards like noise or heat, or delays in the production process. Current Business Process Management (BPM) Systems (BPMS) are not capable of readily taking such factors into account. There- fore, this contribution proposes a novel approach for context- integrated modeling and execution of processes with AR tasks. Our practical evaluations show that our AR Process Framework can be easily integrated with prevalent BPMS. Furthermore, we have created a comprehensive simulation scenario and our findings suggest that the application of this system can lead to various benefits, like better quality of AR task execution and cost savings regarding the overall Industry 4.0 processes.}, language = {en} }