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Trustworthiness-Related Risks in Autonomous Cyber-Physical Production Systems - A Survey

Authors :
Zahid, Maryam
Bucaioni, Alessio
Flammini, Francesco
Zahid, Maryam
Bucaioni, Alessio
Flammini, Francesco
Publication Year :
2023

Abstract

The production industry is looking for new solutions to improve the reliability, safety and efficiency of traditional processes. Current developments in artificial intelligence and machine learning have enabled a high level of autonomy in smart-manufacturing and production systems within Industry 4.0, thus paving the way towards fully Autonomous Cyber-Physical Production Systems (ACPPS). Although ACPPS can have many advantages, there still remains a concern regarding how much we can trust those systems, due to limited predictability, transparency, and explainability, as well as emerging vulnerabilities related to machine learning systems. In this paper, we present the findings of a study conducted on the possible risks related to the trustworthiness of ACPPS, and the consequences they have on the system and its environment.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1416051526
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1109.CSR57506.2023.10224955