From Artificial Intelligence to Explainable Artificial Intelligence in Industry 4.0: A Survey on What, How, and Where

Nowadays, Industry 4.0 can be considered a reality, a paradigm integrating modern technologies and innovations. Artificial intelligence (AI) can be considered the leading component of the industrial transformation enabling intelligent machines to execute tasks autonomously such as self-monitoring, i...

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Vydané v:IEEE transactions on industrial informatics Ročník 18; číslo 8; s. 5031 - 5042
Hlavní autori: Ahmed, Imran, Jeon, Gwanggil, Piccialli, Francesco
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Artificial intelligence
Artificial intelligence (AI)
cloud computing
cyber-physical system
Deep learning
Downtime
Explainable artificial intelligence
explainable artificial intelligence (XAI)
Fourth Industrial Revolution
Hidden Markov models
Industrial applications
Industries
Industry 4.0
Internet of Things (IoT)
Machine learning
Manufacturing
Predictive maintenance
Robots
Service robots
ISSN:1551-3203, 1941-0050
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Shrnutí:Nowadays, Industry 4.0 can be considered a reality, a paradigm integrating modern technologies and innovations. Artificial intelligence (AI) can be considered the leading component of the industrial transformation enabling intelligent machines to execute tasks autonomously such as self-monitoring, interpretation, diagnosis, and analysis. AI-based methodologies (especially machine learning and deep learning support manufacturers and industries in predicting their maintenance needs and reducing downtime. Explainable artificial intelligence (XAI) studies and designs approaches, algorithms and tools producing human-understandable explanations of AI-based systems information and decisions. This article presents a comprehensive survey of AI and XAI-based methods adopted in the Industry 4.0 scenario. First, we briefly discuss different technologies enabling Industry 4.0. Then, we present an in-depth investigation of the main methods used in the literature: we also provide the details of what, how, why, and where these methods have been applied for Industry 4.0. Furthermore, we illustrate the opportunities and challenges that elicit future research directions toward responsible or human-centric AI and XAI systems, essential for adopting high-stakes industry applications.
Bibliografia:ObjectType-Article-1
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ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2022.3146552