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.
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Acknowledgements
The authors would like to thank University Malaysia Pahang Al-Sultan Abdullah for providing financial support and laboratory facilities under Research Development Grant Scheme (RDU) No. 210317 and Postgraduate Research Grant Scheme (PGRS) No. 210336.
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Abd. Ghafar, A.N., Babu, D., Sidik, M.H.M., Rosle, M.H., Ruzlan, N.N. (2024). Intelligent Machining Systems for Robotic End-Effectors: State-of-the-Art and Toward Future Directions. In: Mohd. Isa, W.H., Khairuddin, I.M., Mohd. Razman, M.A., Saruchi, S.'., Teh, SH., Liu, P. (eds) Intelligent Manufacturing and Mechatronics. iM3F 2023. Lecture Notes in Networks and Systems, vol 850. Springer, Singapore. https://doi.org/10.1007/978-981-99-8819-8_7
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