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The paper analyzes how machine learning can reshape industrial workflows to improve efficiency and output while exposing key obstacles, including data requirements and limits in model interpretability. It evaluates blockchain’s potential to strengthen security and transparency, along with risks from attacks and smart-contract weaknesses. 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The paper also notes that success depends on sufficient data and limits in model interpretability.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What role does blockchain technology play, and what risks are highlighted?",{"text":117,"@type":113},"Blockchain is presented as a way to improve industrial security and transparency. The paper also highlights hazards such as possible attacks and smart contract vulnerabilities.",{"name":119,"@type":110,"acceptedAnswer":120},"Which constraints and future opportunities are discussed for additive manufacturing and materials?",{"text":121,"@type":113},"Additive manufacturing—especially 3D printing—is analyzed in terms of challenges like printing speed, product quality, and material availability. The paper further points to potential progress using new materials such as bio-based polymers and 2D heterostructures for robotic systems.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},128557,1786001728,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":81},549768064622,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Roboticsin Manufacturing: Challengesand Future Directions  \nMuhamad Ridzuan Radin Muhamad Amin , Abdul Nasir Abd. Ghafar , Norasilah Karumdin, Ahmad Noor Syukri Zainal Abidin,  \nand Muhammad Nur Farhan Saniman   \nAbstract 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 efficiencyand production while simultaneously highlighting the challenges ofdata 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.  \nKeywords Machine learning · Blockchain technology · Robotics in  \nmanufacturing · Industrial automation · Advanced manufacturing technologies  \nM. R. R. M. Amin · A. N. Abd. Ghafar (B)  \nFaculty of Electrical and Electronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia  \ne-mail: [abdnasir@umpsa.edu.my](abdnasir@umpsa.edu.my)  \nN. Karumdin · A. N. S. Z. Abidin  \nFaculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia  \nM. N. F. Saniman  \nMechanical Engineering Section, Universiti Kuala Lumpur Malaysia France Institute, 43650 Bandar Baru Bangi, Selangor, Malaysia  \n© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024  \nW. H. Mohd Isa et al. (eds.), Intelligent Manufacturing and Mechatronics, Lecture Notes in Networks and Systems 850, [https://doi.org/10.1007/978-981-99-8819-8_5](https://doi.org/10.1007/978-981-99-8819-8_5)  \n61","cbCaihLBphq6WhBD","https://ap.wps.com/l/cbCaihLBphq6WhBD","pdf",50973,"English","# Abstract\n## Industrial robotics and present uses\n## Machine learning challenges\n## Blockchain security and transparency risks\n## Additive manufacturing constraints and future directions","[{\"question\":\"How does machine learning contribute to advanced robotics in manufacturing?\",\"answer\":\"Machine learning is used to change industrial processes, improving efficiency and production outcomes. The paper also notes that success depends on sufficient data and limits in model interpretability.\"},{\"question\":\"What role does blockchain technology play, and what risks are highlighted?\",\"answer\":\"Blockchain is presented as a way to improve industrial security and transparency. The paper also highlights hazards such as possible attacks and smart contract vulnerabilities.\"},{\"question\":\"Which constraints and future opportunities are discussed for additive manufacturing and materials?\",\"answer\":\"Additive manufacturing—especially 3D printing—is analyzed in terms of challenges like printing speed, product quality, and material availability. The paper further points to potential progress using new materials such as bio-based polymers and 2D heterostructures for robotic systems.\"}]","Harnessing Machine Learning, Blockchain, and Digital Twin Technology for Advanced Robotics in Manufacturing - Challenges and Future Directions | PDF"]