SIG HIC - Human Computer Interaction
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Paper Type
Complete
Paper Number
1355
Description
Advances in technologies, such as the Internet of Things (IoT) and Visual Analytics (VA), are enabling a new generation of smart manufacturing. These technologies enable the efficient tracking of the quality of produced parts along every step in the manufacturing process. However, the challenge remains that distinct IoT data sources must be connected, harmonized, and made readily accessible to human experts for analyses. In this paper, we followed a design science research approach to develop a VA artifact supporting engineering experts in analyzing IoT data from interconnected stations of a manufacturing process for electrical engines. We developed our artifact in collaboration with an industrial partner from the automotive sector and evaluated it with five engineering experts. Results indicate high usability and usefulness of the artifact as part of a real-world manufacturing process. Our instantiated artifact can serve as guidance to researchers and practitioners, who work in similar manufacturing domains.
Recommended Citation
Eirich, Joscha, "Visual Analytics for IoT Data From Large-Scale Manufacturing Processes" (2022). AMCIS 2022 Proceedings. 9.
https://aisel.aisnet.org/amcis2022/sig_hci/sig_hci/9
Visual Analytics for IoT Data From Large-Scale Manufacturing Processes
Advances in technologies, such as the Internet of Things (IoT) and Visual Analytics (VA), are enabling a new generation of smart manufacturing. These technologies enable the efficient tracking of the quality of produced parts along every step in the manufacturing process. However, the challenge remains that distinct IoT data sources must be connected, harmonized, and made readily accessible to human experts for analyses. In this paper, we followed a design science research approach to develop a VA artifact supporting engineering experts in analyzing IoT data from interconnected stations of a manufacturing process for electrical engines. We developed our artifact in collaboration with an industrial partner from the automotive sector and evaluated it with five engineering experts. Results indicate high usability and usefulness of the artifact as part of a real-world manufacturing process. Our instantiated artifact can serve as guidance to researchers and practitioners, who work in similar manufacturing domains.
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