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Model Based Trustworthiness Evaluation of Autonomous Cyber-Physical Production Systems: A Systematic Mapping Study
Publication Type:
Journal article
Venue:
ACM Computing Surveys
Abstract
The fourth industrial revolution, i.e., Industry 4.0, is associated with Cyber-Physical Systems (CPS), which are entities integrating
hardware (e.g., smart sensors and actuators connected through the Industrial Internet of Things) together with control and analytics
software used to drive and support decisions at several levels. The latest developments in Artificial Intelligence (AI) and Machine
Learning (ML) have enabled increased autonomy and closer human-robot cooperation in the production and manufacturing industry,
thus leading to Autonomous Cyber-Physical Production Systems (ACPPS), and paving the way to the fifth industrial revolution (i.e.,
Industry 5.0). ACPPS are increasingly critical due to the possible consequences of their malfunctions on human co-workers, and
therefore evaluating their trustworthiness is essential. In this paper, we review research trends, relevant attributes, modeling languages,
and tools related to the model-based trustworthiness evaluation of ACPPS. As in many other engineering disciplines and domains,
model-based approaches including stochastic and formal analysis tools are essential to master the increasing complexity and criticality
of ACPPS and to prove relevant attributes such as system safety in the presence of intelligent behaviors and uncertainties.
Bibtex
@article{Zahid6856,
author = {Maryam Zahid and Alessio Bucaioni and Francesco Flammini},
title = {Model Based Trustworthiness Evaluation of Autonomous Cyber-Physical Production Systems: A Systematic Mapping Study},
volume = {1},
pages = {1--28},
month = {January},
year = {2024},
journal = {ACM Computing Surveys},
url = {http://www.ipr.mdu.se/publications/6856-}
}