- Ricardo J. Rabelo ORCID:orcid.org/0000-0002-5488-369219,
- Lara P. Zambiasi ORCID:orcid.org/0000-0003-4644-318419,20,22,
- Saulo P. Zambiasi ORCID:orcid.org/0000-0002-7694-487121,
- Mina Foosherian ORCID:orcid.org/0000-0002-2399-621322,
- Stefan Wellsandt ORCID:orcid.org/0000-0002-0797-071822,
- David Romero ORCID:orcid.org/0000-0003-3610-075123 &
- …
- Karl Hribernik ORCID:orcid.org/0000-0002-3567-589822
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Abstract
Industry 4.0/5.0 workplaces are characterized by humans surrounded by massive digitalization, huge data generation, and data-driven management. However, this brings more complexity to the operators as they are exposed to vast amounts of data to reason about as well as to many situations of overwhelming cognitive load, leading them to potentially less assertive and stressful decision-making. This becomes challenging when operators should manage two or more machines simultaneously as in a ‘One-Worker-Multiple-Machines’ (OWMM) working environment, including critical processes and equipment. This paper proposes a softbot approach to address these issues devising an OWMM smart cockpit environment where an intelligent softbot supports an operator in several production situations. A software prototype was developed to show the potential and benefits of the softbot approach in OWMM environments.
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Notes
- 1.
ARISA NEST tool for softbot derivations –https://arisa.com.br/ [in Portuguese].
- 2.
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Acknowledgments
This work has been partially funded by (i) CAPES, The Brazilian Agency for Higher Education, project PrInt “Automation 4.0” and “Finance Code 001”, and (ii) the European Union’s Horizon Europe project WASABI “White-label shop floor digital intelligent assistance and human-AI collaboration in manufacturing” (GA 101092176). The authors thank Mr. Bruno T. Guedes, the Hightech company’s engineer (www.hightech.ind.br), for having provided the information that mainly served for the scenarios’ conception of this work.
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Authors and Affiliations
UFSC – Federal University of Santa Catarina, Florianópolis, Brazil
Ricardo J. Rabelo & Lara P. Zambiasi
IFSC – Federal Institute of Santa Catarina, Chapecó, Brazil
Lara P. Zambiasi
UNISUL – University of the South of Santa Catarina, Florianópolis, Brazil
Saulo P. Zambiasi
BIBA at the University of Bremen, Hochschulring 20, 28359, Bremen, Germany
Lara P. Zambiasi, Mina Foosherian, Stefan Wellsandt & Karl Hribernik
Tecnológico de Monterrey, Mexico City, Mexico
David Romero
- Ricardo J. Rabelo
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- Lara P. Zambiasi
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- Stefan Wellsandt
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Correspondence toRicardo J. Rabelo.
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Chemnitz University of Technology, Chemnitz, Germany
Matthias Thürer
West Saxon University of Applied Sciences Zwickau, Zwickau, Germany
Ralph Riedel
ZF Friedrichshafen AG, Friedrichshafen, Germany
Gregor von Cieminski
Tecnológico de Monterrey, Mexico City, Mexico
David Romero
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Rabelo, R.J.et al. (2024). Augmenting the One-Worker-Multiple-Machines System: A Softbot Approach to Support the Operator 5.0. In: Thürer, M., Riedel, R., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments. APMS 2024. IFIP Advances in Information and Communication Technology, vol 729. Springer, Cham. https://doi.org/10.1007/978-3-031-65894-5_25
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