Abstract
There is a lack of a single architecture specification that addresses the needs of trusted and secure Artificial Intelligence systems with humans in the loop, such as human-centered manufacturing systems at the core of the evolution towards Industry 5.0. To realize this, we propose an architecture that integrates forecasts, Explainable Artificial Intelligence, supports collecting users’ feedback and uses Active Learning and Simulated Reality to enhance forecasts and provide decision-making recommendations. The architecture security is addressed at all levels. We align the proposed architecture with the Big Data Value Association Reference Architecture Model. We tailor it for the domain of demand forecasting and validate it on a real-world case study.
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Notes
- 1.
A video of the application was published in https://youtu.be/ysD2oXQO98I.
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Acknowledgement
This work was supported by the Slovenian Research Agency and the European Union’s Horizon 2020 program projects FACTLOG and STAR under grant agreements numbers H2020-869951 and H2020-956573.
This document is the property of the STAR consortium and shall not be distributed or reproduced without the formal approval of the STAR Management Committee. The content of this report reflects only the authors’ view. The European Commission is not responsible for any use that may be made of the information it contains.
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Rožanec, J.M. et al. (2021). STARdom: An Architecture for Trusted and Secure Human-Centered Manufacturing Systems. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-030-85910-7_21
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