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Explainable AI in Manufacturing and Industrial Cyber–Physical Systems: A Survey.

Authors :
Moosavi, Sajad
Farajzadeh-Zanjani, Maryam
Razavi-Far, Roozbeh
Palade, Vasile
Saif, Mehrdad
Source :
Electronics (2079-9292); Sep2024, Vol. 13 Issue 17, p3497, 28p
Publication Year :
2024

Abstract

This survey explores applications of explainable artificial intelligence in manufacturing and industrial cyber–physical systems. As technological advancements continue to integrate artificial intelligence into critical infrastructure and industrial processes, the necessity for clear and understandable intelligent models becomes crucial. Explainable artificial intelligence techniques play a pivotal role in enhancing the trustworthiness and reliability of intelligent systems applied to industrial systems, ensuring human operators can comprehend and validate the decisions made by these intelligent systems. This review paper begins by highlighting the imperative need for explainable artificial intelligence, and, subsequently, classifies explainable artificial intelligence techniques systematically. The paper then investigates diverse explainable artificial-intelligence-related works within a wide range of industrial applications, such as predictive maintenance, cyber-security, fault detection and diagnosis, process control, product development, inventory management, and product quality. The study contributes to a comprehensive understanding of the diverse strategies and methodologies employed in integrating explainable artificial intelligence within industrial contexts. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20799292
Volume :
13
Issue :
17
Database :
Complementary Index
Journal :
Electronics (2079-9292)
Publication Type :
Academic Journal
Accession number :
179647007
Full Text :
https://doi.org/10.3390/electronics13173497