Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions
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 th...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Springer Nature
2024
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/41146/ http://umpir.ump.edu.my/id/eprint/41146/1/Harnessing%20Machine%20Learning%2C%20Blockchain%2C%20and%20Digital%20Twin%20Technology%20for%20Advanced%20Robotics%20in%20Manufacturing.pdf http://umpir.ump.edu.my/id/eprint/41146/2/Harnessing%20Machine%20Learning%2C%20Blockchain%2C%20and%20Digital%20Twin%20Technology%20for%20Advanced%20Robotics%20in%20Manufacturing%20-%20Challenges%20and%20Future%20Directions.pdf |
| _version_ | 1848826249889185792 |
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| author | Muhamad Ridzuan, Radin Muhamad Amin Abdul Nasir, Abd Ghafar Norasilah, Karumdin Ahmad Noor Syukri, Zainal Abidin Muhammad Nur Farhan, Saniman |
| author_facet | Muhamad Ridzuan, Radin Muhamad Amin Abdul Nasir, Abd Ghafar Norasilah, Karumdin Ahmad Noor Syukri, Zainal Abidin Muhammad Nur Farhan, Saniman |
| author_sort | Muhamad Ridzuan, Radin Muhamad Amin |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T03:41:49Z |
| format | Conference or Workshop Item |
| id | ump-41146 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:41:49Z |
| publishDate | 2024 |
| publisher | Springer Nature |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-411462024-05-16T04:25:23Z http://umpir.ump.edu.my/id/eprint/41146/ Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions Muhamad Ridzuan, Radin Muhamad Amin Abdul Nasir, Abd Ghafar Norasilah, Karumdin Ahmad Noor Syukri, Zainal Abidin Muhammad Nur Farhan, Saniman TK Electrical engineering. Electronics Nuclear engineering TS Manufactures 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. Springer Nature 2024 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/41146/1/Harnessing%20Machine%20Learning%2C%20Blockchain%2C%20and%20Digital%20Twin%20Technology%20for%20Advanced%20Robotics%20in%20Manufacturing.pdf pdf en http://umpir.ump.edu.my/id/eprint/41146/2/Harnessing%20Machine%20Learning%2C%20Blockchain%2C%20and%20Digital%20Twin%20Technology%20for%20Advanced%20Robotics%20in%20Manufacturing%20-%20Challenges%20and%20Future%20Directions.pdf 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 (Published) https://doi.org/10.1007/978-981-99-8819-8_5 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Muhamad Ridzuan, Radin Muhamad Amin Abdul Nasir, Abd Ghafar Norasilah, Karumdin Ahmad Noor Syukri, Zainal Abidin Muhammad Nur Farhan, Saniman Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions |
| title | Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions |
| title_full | Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions |
| title_fullStr | Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions |
| title_full_unstemmed | Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions |
| title_short | Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing: Challenges and Future Directions |
| title_sort | harnessing machine learning, blockchain, and digital twin technology for advanced robotics in manufacturing: challenges and future directions |
| topic | TK Electrical engineering. Electronics Nuclear engineering TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/41146/ http://umpir.ump.edu.my/id/eprint/41146/ http://umpir.ump.edu.my/id/eprint/41146/1/Harnessing%20Machine%20Learning%2C%20Blockchain%2C%20and%20Digital%20Twin%20Technology%20for%20Advanced%20Robotics%20in%20Manufacturing.pdf http://umpir.ump.edu.my/id/eprint/41146/2/Harnessing%20Machine%20Learning%2C%20Blockchain%2C%20and%20Digital%20Twin%20Technology%20for%20Advanced%20Robotics%20in%20Manufacturing%20-%20Challenges%20and%20Future%20Directions.pdf |