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

• Main Authors: Abdul Nasir, Abd Ghafar, Babu, Devin, Mohd Hanafi, Muhammad Sidik, Muhammad Hisyam, Rosle, Nurul Najwa, Ruzlan
• Format: Conference or Workshop Item
• Language: English; English
• Published: Springer Singapore 2024
• Subjects: TJ Mechanical engineering and machinery; TK Electrical engineering. Electronics Nuclear engineering; TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/41196/1/Intelligent%20Machining%20Systems%20for%20Robotic%20End-Effectors_%20State-of-the-Art%20and%20Toward%20Future%20Directions.pdf; http://umpir.ump.edu.my/id/eprint/41196/2/Intelligent%20Machining%20Systems%20for%20Robotic%20End-Effectors_%20State-of-the-Art%20and%20Toward%20Future%20Directions%20ALL.pdf; http://umpir.ump.edu.my/id/eprint/41196/; https://doi.org/10.1007/978-981-99-8819-8_7

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.