Industrial Automation: State-of-the-Art Technologies and Future Directions
Abstract
Industrial automation is experiencing a seismic transformation fueled by an array of cutting-edge technologies. This review explores the forefront of innovation in industrial automation, encompassing an eclectic mix of advancements revolutionizing manufacturing landscapes. From robotics and IoT to quantum computing and cognitive automation, these state-of-the-art technologies redefine efficiency, precision, and sustainability in industrial operations. The integration of AI, edge computing, and advanced materials reshapes traditional paradigms, ushering in an era of predictive maintenance, remote monitoring, and autonomous decision-making. This comprehensive overview not only encapsulates the current technological zenith but also anticipates a future where human-machine collaboration and sustainable practices harmoniously converge to drive industrial evolution.
References
2. Berman B. 3-D Printing: The New Industrial Revolution.Business Horizons, 2018; 61(4): 545-553.
3. Fossey J The Role of IoT in Supply Chain Management:A Comprehensive Review. Journal of OperationsManagement, 2021; 29(3):78-94
4. Grieves M. Digital Twins: Concepts and Practices. BocaRaton, FL: CRC Press 2019.
5. Hoff N. Industrial Automation and Cyber-PhysicalSystems: A Comprehensive Overview. IEEE Transactionson Industrial Informatics, 2020; 15(5): 2325-2341.
6. Jiang J, Zhou M. Edge Computing in IndustrialAutomation: Concepts and Challenges. IEEETransactions on Industrial Informatics, 2018; 14(3):1208-1220.
7. Jiang J, Zhou M. Edge Computing in IndustrialAutomation: Concepts and Challenges. IEEETransactions on Industrial Informatics, 2018; 14(3):1208-1220.
8. Kusiak A. Smart Manufacturing. International Journalof Production Research, 2017; 55(15): 4257-4272.
9. Lee J, Lapira E. Industrial Big Data Analytics and Cyber-Physical Systems for Future Maintenance & ServiceInnovation in Industries. Computers & IndustrialEngineering, 2019; 139, 106120.
10. Lu Y, Morris K. The Role of Artificial Intelligence inFuture Industrial Automation Systems. Robotics andComputer-Integrated Manufacturing, 2018; 48, 1-9.
11. National Institute of Standards and Technology. ARoadmap for Sustainable Manufacturing. NIST Special
Publication 800-162 2019.
12. Pan Y, Xu Y. Additive Manufacturing in Industry 4.0:
From Design Principles to Product Realization. Journalof Manufacturing Science and Engineering, 2020;142(5): 050801.
13. Rathore M, Sharma G. Virtual and Augmented Reality inManufacturing: A Comprehensive Review. Computersin Industry, 2019; 108, 102-114.
14. Saif U, Ceccarelli M. Collaborative Robotics: FuturePerspectives in Intelligent Manufacturing. IFToMMWorld Congress on Mechanism and Machine Science,53-65 2017.
15. Soley R, Schutz M. Blockchain in Manufacturing:Promise, Practice, and Application. ManufacturingLetters, 2021; 29, 23-28.
16. Sundar V, Lyer N. AI and Machine Learning in IndustrialIoT: A Review. Journal of Industrial InformationIntegration, 2018; 10, 1-9.
17. Tayur S. Sustainable Manufacturing: Frameworks andPractices. New York, NY: Routledge 2019.
18. Törngren M, Riliskis L. Future Challenges in Cyber-
Physical Systems Engineering for Industrial Automation.IFAC-PapersOnLine, 2019; 52(13): 183-188.
19. Vatankhah Barenji, R, Parlikad A. Edge Computing andIts Application in Industrial Automation: A Review.Annual Reviews in Control, 2020; 50, 91-103.
20. Wang X, Vakanski A. Robotic Automation inManufacturing: A Review. IEEE Access, 6, 61225-61245
2018
