On the ISO Compliance of Model-Based Risk Assessment for Autonomous Cyber-Physical Production Systems

Industrial digitalization has led to the introduction of autonomous cyber-physical production systems, optimizing the production processes. Stakeholders, however, are becoming concerned about the trustworthiness of such systems, especially its safety and the safety of its users. Over the years, many model-based risk assessment techniques have been proposed to help mitigate the trustworthiness-related risks within the targeted systems. However, these techniques do not meet the requirements of the guidelines provided by the International Standardization Organization have. Moreover, these techniques fail to consider the possible risks from the machine learning component of autonomous cyber-physical production systems. As a contribution, this paper presents an analysis of the compliance of MATrICS with the relevant ISO standards, its adaptation to ensure compliance, and its validation.

Authors

Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/csr61664.2024.10679385
Citations
2
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the ISO Compliance of Model-Based Risk Assessment for Autonomous Cyber-Physical Production Systems

Francesco Flammini, Alessio Bucaioni, Maryam Zahid
2 citations
Digital Transformation in Industry
0.70
article

On the ISO Compliance of Model-Based Risk Assessment for Autonomous Cyber-Physical Production Systems

Francesco Flammini, Alessio Bucaioni, Maryam Zahid
article en
2 citations

Abstract

Industrial digitalization has led to the introduction of autonomous cyber-physical production systems, optimizing the production processes. Stakeholders, however, are becoming concerned about the trustworthiness of such systems, especially its safety and the safety of its users. Over the years, many model-based risk assessment techniques have been proposed to help mitigate the trustworthiness-related risks within the targeted systems. However, these techniques do not meet the requirements of the guidelines provided by the International Standardization Organization have. Moreover, these techniques fail to consider the possible risks from the machine learning component of autonomous cyber-physical production systems. As a contribution, this paper presents an analysis of the compliance of MATrICS with the relevant ISO standards, its adaptation to ensure compliance, and its validation.

Openalex Percentile: Top 26%
Digital Transformation in Industry
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.