Intelligent Machining Systems for Robotic End-Effectors: State-of-the-Art and Toward Future Directions

Abdul Nasir, Abd Ghafar and Babu, Devin and Mohd Hanafi, Muhammad Sidik and Muhammad Hisyam, Rosle and Nurul Najwa, Ruzlan (2024) Intelligent Machining Systems for Robotic End-Effectors: State-of-the-Art and Toward 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. 83-93., 850. ISSN 2367-3389 ISBN 978-981-99-8819-8 (Published)

[img]
Preview
Pdf
Intelligent Machining Systems for Robotic End-Effectors_ State-of-the-Art and Toward Future Directions.pdf

Download (50kB) | Preview
[img] Pdf
Intelligent Machining Systems for Robotic End-Effectors_ State-of-the-Art and Toward Future Directions ALL.pdf
Restricted to Repository staff only

Download (364kB) | Request a copy

Abstract

This review paper delves into the advancements brought about by Industry 4.0 in the realm of intelligent machining systems for robotic end-effectors. Robotic end-effectors, which are the devices at the end of a robotic arm, have seen significant enhancements in their design, development, and application across various sectors, from manufacturing to healthcare. The integration of intelligent machining systems into these end-effectors has augmented their efficiency, precision, and flexibility. The paper also highlights the role of intelligent control systems in boosting the performance of these robotic systems. Despite the progress, challenges persist, such as improving machining accuracy, optimizing machining trajectories, and integrating machine learning techniques. The review concludes by identifying gaps in the current research and suggests potential areas for future exploration to further enhance the capabilities of robotic end-effectors.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Robotic end-effectors; Intelligent machining systems; Intelligent control systems; Compliance control; Machining trajectory optimization
Subjects: T Technology > TJ Mechanical engineering and machinery
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
Faculty of Mechanical and Automotive Engineering Technology
Depositing User: Miss Amelia Binti Hasan
Date Deposited: 16 May 2024 02:29
Last Modified: 16 May 2024 04:23
URI: http://umpir.ump.edu.my/id/eprint/41196
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item