Abstract
Production management involves many activities. In order to deal with Industry 4.0 requirements, many systems have developed solutions to gather real-time information from the shopfloor for more reliable decision-making. Empirical studies have been showing that this has created a tremendous overload of information to be handled by managers, causing stress, incorrect analyses and sometimes guessing-based decision-making, especially in SMEs. Using data analytics and maturity models concepts, this work shows Livia, a softbot with chatting capabilities. Deployed in a cloud and working on companies’ shopfloor information got via a MES system, Livia helps managers to identify their main problems, suggests corrective actions, and proactively performs many supporting actions. Results are presented and discussed in the end.
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Notes
- 1.
- 2.
- 3.
The name Livia comes from the union of LiveMES with the intelligent analysis words.
- 4.
ARISA NEST tool for softbots derivation – https://arisa.com.br/ [in Portuguese].
- 5.
- 6.
All the conversations and figures’ texts were translated ipsis litteris to English only for the purpose of this paper. All the liveMES and Livia user interfaces are written in Portuguese.
- 7.
A work center can embrace one or more machines, depending on local installations.
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Acknowledgements
This work has been partially supported by CAPES Brazilian Agency for Higher Education, project PrInt “Automation 4.0”. Authors would like to thank Harbor company and their managers, Mr. Paulo Narciso and Mr. Tulio Duarte, for the deep support to this work.
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Abner, B., Rabelo, R.J., Zambiasi, S.P., Romero, D. (2020). Production Management as-a-Service: A Softbot Approach. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Towards Smart and Digital Manufacturing. APMS 2020. IFIP Advances in Information and Communication Technology, vol 592. Springer, Cham. https://doi.org/10.1007/978-3-030-57997-5_3
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