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Abstract
When considering how an intelligent factory can ‘see,’ the answer lies in machine vision technology. To assess the current technological advancements of machine vision systems and propose a technology maturity assessment framework, a nine-phase Systematic Literature Review (SLR) strategy was implemented. As the automotive industry stands at the forefront of autonomous systems, we analysed 85 works across the entire automotive manufacturing life cycle. The findings revealed that machine vision is utilised in each technological pillar of Industry 4.0, encompassing autonomous robots, augmented reality, predictive maintenance, additive manufacturing, and more. In analysing 22 vision-based applications in 47 automotive components, we clustered machine vision systems' architectural components and processing techniques, ranging from threshold-based methods to advanced reinforcement learning techniques suitable for the I5.0 environment. Leveraging the insights gathered, we propose the I5.0 technology maturity assessment framework for machine vision systems, evaluating nine functional components across five scaling technology levels. This framework serves as a valuable tool to identify weaknesses and opportunities for improvement, guiding machine vision integration into an intelligent factory.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Data sharing not applicable – no new data generated
Notes
Additional information
Notes on contributors
Fotios K. Konstantinidis
Fotios Konstantinidis is a Team leader in Industry 5.0 & Smart Manufacturing at the Institute of Communication and Computer Systems (ICCS) of the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) and holds a Ph.D. in Smart Manufacturing from the department of Production & Management Engineering at the Democritus University of Thrace (DUTh). He is currently leading a team of researchers and professionals with the objective of developing advanced industrial waste sorting systems. These systems utilize cutting-edge technologies such as hyperspectral & visual imaging, delta robots, air nozzles, X-ray sensors, and pretreatment units. Their focus areas include the efficient sorting of (bio)plastic waste, construction and demolition waste, metal scraps, mining characterization, and wood waste. Before this, Fotios worked as an I4.0 Technology Analyst, analysing the plants' maturity level and proposing I4.0 strategies for Fortune 500 companies. In contrast, he worked in the telecom industry at the Next-Generation Access networks. He has also organised workshops, delivered presentations at conferences/workshops, and published peer-reviewed journal papers throughout his career.
Nikolaos Myrillas
Nikolaos Myrillas is a graduate of the Democritus University of Thrace. He holds a bachelor's degree in Production and Management Engineering. His research focuses on Industry 4.0 (I4.0) and advanced manufacturing technologies during the fourth industrial revolution. This was also the topic of his thesis, which was conducted as a final step of his studies. Nikolaos has worked in EYDAP S.A. - ATHENS WATER SUPPLY AND SEWERAGE COMPANY as an intern, where he gained exposure to the sustainable management practices of EYDAP through training on the exploitation of its renewable energy resource facilities. Nikolaos is not yet that experienced, but his love and passion for I4.0-related topics are guiding him.
Konstantinos A. Tsintotas
Konstantinos Tsintotas (Senior Member, IEEE) received a bachelor's degree from the Department of Automation Engineering, Technological Education Institute of Chalkida (now National and Kapodistrian University of Athens), Psachna, Greece, in 2010, the master's degree in mechatronics from the Department of Electrical Engineering, Technological Education Institute of Western Macedonia (now University of Western Macedonia), Kila Kozanis, Greece, in 2015, and the Doctoral degree in robotics from the Department of Production and Management Engineering, Democritus University of Thrace, Xanthi, Greece, in 2021. He is currently a Postdoctoral researcher with the Laboratory of Robotics and Automation, Department of Production and Management Engineering, Democritus University of Thrace. His work is supported by several research projects funded by the European Commission and the Greek Government. His research interests include vision-based methods for modern and intelligent mechatronics systems. Details are available at: https://robotics.pme.duth.gr/ktsintotas
Spyridon G. Mouroutsos
Spyridon Mouroutsos received the Diploma in Electrical Engineering from the Democritus University of Thrace, Greece (1981) and his Ph.D. in Systems Automation from the same University (1986). In 1986, he joined, as an Assistant Professor, the Electrical and Computer Engineering Department at the Democritus University of Thrace, Greece, where he currently serves as a Professor in Mechatronics, Systems Automation, and Standards. He has been a Referee, a Committee Member, or a Member of the Editorial Board for numerous International Scientific and Technical Journals and Conferences. Moreover, he has acted as an evaluator for National and EU research grant applications. His research interests include applications in Mechatronics, Systems Automation and Robotics, Intelligent and autonomous robots (humanoids, animated, underwater, flying, etc.), Data Fusion - sensors with applications in robotics and automation, Computer architectures - microprocessors and their applications and also Standards and Certification
Antonios Gasteratos
Antonios Gasteratos (Fellow member IET, Senior member IEEE) received the M.Eng. and Ph.D. degrees from the Department of Electrical and Computer Engineering, Democritus University of Thrace (DUTh), Xanthi, Greece, in 1994 and 1998, respectively. From 1999 to 2000, he was a Visiting Researcher with the Laboratory of Integrated Advanced Robotics (LIRALab), DIST, University of Genoa, Genoa, Italy. He is currently a Professor and the Head of the Production and Management Engineering Department, DUTh. He is also the Director of the Laboratory of Robotics and Automation, DUTh, and teaches robotics, automatic control systems, electronics, mechatronics, and computer vision courses. He has authored more than 220 books, journals, and conference papers. His research interests include mechatronics and robot vision. Dr. Gasteratos is a Fellow member of IET. He has served as a reviewer for numerous scientific journals and international conferences. He is a Subject Editor of Electronics Letters and an Associate Editor of the International Journal of Optomechatronics. He has organised/co-organised several international conferences. More details about him are available at http://robotics.pme.duth.gr/antonis.