Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions

Muhamad Ridzuan, Radin Muhamad Amin and Abdul Nasir, Abd Ghafar and Norasilah, Karumdin and Ahmad Noor Syukri, Zainal Abidin and Muhammad Nur Farhan, Saniman (2024) Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions. In: Intelligent Manufacturing and Mechatronics, Lecture Notes in Networks and Systems. 4th International conference on Innovative Manufacturing, Mechatronics and Materials Forum, iM3F2023 , 07 – 08 August 2023 , Pekan, Malaysia. pp. 61-70., 850. ISSN 2367-3389 ISBN 978-981-99-8819-8

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Abstract

This paper digs into robots’ revolutionary role in the industrial landscape, highlighting present uses and future trends while addressing ongoing problems. It investigates how machine learning is altering industrial processes, increasing efficiency and production while simultaneously highlighting the challenges of data needs and model interpretability. The evaluation investigates the promise of blockchain technology in enhancing industrial security and transparency, while also recognizing the hazards of possible attacks and smart contract vulnerabilities. The transformational influence of additive manufacturing, particularly 3D printing, is discussed, as well as the constraints connected with printing speed, product quality, and material availability. The study emphasizes the potential of new materials such as bio-based polymers and 2D heterostructures in the advancement of robotic systems. Despite these encouraging achievements, the assessment finds gaps in existing research and suggests future strategies for maximizing the potential of these technologies in the industrial industry.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Machine learning; Blockchain technology; Robotics in manufacturing; Industrial automation; Advanced manufacturing technologies
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures
Faculty/Division:	Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Miss Amelia Binti Hasan
Date Deposited:	09 May 2024 06:05
Last Modified:	16 May 2024 04:25
URI:	http://umpir.ump.edu.my/id/eprint/41146
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