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STARdom: an architecture for trusted and secure human-centered manufacturing systems

Authors :
Rožanec, Jože M.
Zajec, Patrik
Kenda, Klemen
Novalija, Inna
Fortuna, Blaž
Mladenić, Dunja
Veliou, Entso
Papamartzivanos, Dimitrios
Giannetsos, Thanassis
Menesidou, Sofia Anna
Alonso, Rubén
Cauli, Nino
Recupero, Diego Reforgiato
Kyriazis, Dimosthenis
Sofianidis, Georgios
Theodoropoulos, Spyros
Soldatos, John
Publication Year :
2021

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 as a general concern. 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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2104.00983
Document Type :
Working Paper