TY - JOUR
T1 - The artificial intelligence technologies in Industry 4.0
T2 - A taxonomy, approaches, and future directions
AU - Alenizi, Farhan A.
AU - Abbasi, Shirin
AU - Hussein Mohammed, Adil
AU - Masoud Rahmani, Amir
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/11
Y1 - 2023/11
N2 - Industry 4.0 transforms the manufacturing sector with dynamic, networked, complex industrial environments. These environments generate vast amounts of data and require technology and Artificial Intelligence (AI) to achieve intelligent, efficient, and sustainable production processes. This paper comprehensively reviews 45 articles on AI and Industry 4.0 integration. We propose a taxonomy for AI in Industry 4.0 and classify approaches into Industry 4.0 design and product quality control methods. Our analysis shows that 58% of papers use product quality control methods. Besides, this paper identifies challenges and open issues by illuminating the current landscape. The findings showed that machine learning is the most common AI method for improving Industry 4.0 with 41%, and Python is the most used tool for simulation.
AB - Industry 4.0 transforms the manufacturing sector with dynamic, networked, complex industrial environments. These environments generate vast amounts of data and require technology and Artificial Intelligence (AI) to achieve intelligent, efficient, and sustainable production processes. This paper comprehensively reviews 45 articles on AI and Industry 4.0 integration. We propose a taxonomy for AI in Industry 4.0 and classify approaches into Industry 4.0 design and product quality control methods. Our analysis shows that 58% of papers use product quality control methods. Besides, this paper identifies challenges and open issues by illuminating the current landscape. The findings showed that machine learning is the most common AI method for improving Industry 4.0 with 41%, and Python is the most used tool for simulation.
KW - Artificial intelligence
KW - Industry 4.0
KW - Internet of Things
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85173903653&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2023.109662
DO - 10.1016/j.cie.2023.109662
M3 - Article
AN - SCOPUS:85173903653
SN - 0360-8352
VL - 185
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
M1 - 109662
ER -