Enabling Industry 4.0 through Advances in Mechatronics
Selected Articles from iM3F 2021, Malaysia
(Sprache: Englisch)
This book presents part of the iM3F 2021 proceedings from the mechatronics track. It highlights key challenges and recent trends in mechatronics engineering and technology that are non-trivial in the age of Industry 4.0. It discusses traditional as well as...
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This book presents part of the iM3F 2021 proceedings from the mechatronics track. It highlights key challenges and recent trends in mechatronics engineering and technology that are non-trivial in the age of Industry 4.0. It discusses traditional as well as modern solutions that are employed in the multitude spectra of mechatronics-based applications. The readers are expected to gain an insightful view on the current trends, issues, mitigating factors as well as solutions from this book.
Inhaltsverzeichnis zu „Enabling Industry 4.0 through Advances in Mechatronics “
Mapping and Navigation for Indoor Robot Using Multiple Sensor Under ROS Framework.- Optimization of Waterjet Paint Removal Operation using Artificial Neural Network.- Light Path Simulation for Optical Switch Based on Digital Electromagnetic Actuators.- An Application of Charge-Coupled Device (CCD) Tomography System for Gemological Industry - A Review.- Prediction of Abrasive Waterjet Machining of Sheet Metals using Artificial Neural Network.- You Are Too Loud! Classification of Psychological Conditions for Stress Detection System using Galvanic Skin Response.- Universiti Malaysia Pahang Autonomous Shuttle Development: Lane Classification Analysis using Convolutional Neural Network (CNN).- Eco-Design of Electric Vehicle Battery Pack for Ease of Disassembly.- Electric Vehicle Drive Specification Modelling for Three Wheels Scooter Configuration.- Experimentation on Spectra Data Regression using Dense Multilayer Neural Networks with Common Pre-processing.
Autoren-Porträt
Dr. Ismail Mohd Khairuddin is a lecturer at Universiti Malaysia Pahang. He received his Bachelor's Degree in Mechatronics Engineering from Universiti Teknikal Malaysia Melaka (UTeM) in 2010 and was awarded with a Master's Degree in Mechatronics and Automatic Control from Universiti Teknologi Malaysia in 2012. Then, he pursued his Ph.D. studies in Biomechatronics Engineering at the International Islamic University Malaysia. His research interests include rehabilitation robotics, mechanical and mechatronics design, mechanisms, control and automation, bio-signal processing as well as machine learning.Muhammad Amirul bin Abdullah is a researcher at Innovative Manufacturing, Mechatronics & Sports Laboratory (iMAMS), Faculty of Manufacturing and Mechatronic Engineering Technology in Universiti Malaysia Pahang (UMP). He was awarded a Master's Degree and received his Bachelor's Degree, both in Mechatronics Engineering, from International Islamic University Malaysia (IIUM). His research interest includes machine learning, robotics, control and automation, and sports engineering.
Dr. Ahmad Fakhri bin Ab. Nasir received his Bachelor's Degree in Information Technology from Universiti Malaya. He enrolled as a full-time master student at the Faculty of Manufacturing Engineering, Universiti Malaysia Pahang, and received his Master's Degree in Engineering (Manufacturing). He pursued his Ph.D. specialized in Pattern Recognition at the Universiti Sultan Zainal Abidin. He joined Universiti Malaysia Pahang as a senior lecturer at the midst of 2016. He has published several articles and actively doing research related to computer vision, pattern recognition, image processing, machine learning, as well as parallel computing.
Dipl. Ing. (FH) Jessnor Arif Mat Jizat is a researcher at Innovative Manufacturing, Mechatronics & Sports Laboratory, Faculty of Manufacturing and Mechatronic Engineering Technology in Universiti Malaysia Pahang (UMP). He is currently pursuing his Ph.D.
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in Mechatronic Engineering in UMP. Prior to that, he completed his Master's Degree at UMP and Diplom(FH) at Hochschule Karlsruhe, Germany. His research interest includes machine learning, robotics, robotic vision, and sports engineering. He is currently involved in wafer defect detection research in collaboration with Ideal Vision Integration Sdn Bhd and Dzuki Consultancy and Training. He had been appointed as a reviewer for the Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2019, The International Conference of Robotics Intelligence and Applications (RiTA) 2018, Malaysian Journal of Movement, Health & Exercise, and SN Applied Sciences Journal. He also had been appointed as an editor for Lecture Notes in Electrical Engineering 678 Embracing Industry 4.0 - Selected Articles from MUCET 2019 and Lecture Notes in Mechanical Engineering RITA 2018: Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications and as a guest editor for SN Applied Sciences Topical Collection: Engineering - Recent Trends in Electrical & Electronics Engineering.
Dr. Mohd Azraai Mohd Razman graduated his first degree from the University of Sheffield, UK, in Mechatronics Engineering. He then obtained his M.Eng. from Universiti Malaysia Pahang (UMP) in Mechatronics Engineering as well. He then completed his Ph.D. at UMP specifically in the application of machine learning in aquaculture. His research interest includes optimization techniques, control systems, signal processing, instrumentation in aquaculture, sports engineering as well as machine learning. He is currently serving as a guest editor for SN Applied Sciences in a number of topical collections. He has also edited a number of volume in Springer's LNEE and AISC series. He is currently serving as the editor-in-chief for MEKATRONIKA: Journal of Mechatronics and Intelligent Manu
Dr. Mohd Azraai Mohd Razman graduated his first degree from the University of Sheffield, UK, in Mechatronics Engineering. He then obtained his M.Eng. from Universiti Malaysia Pahang (UMP) in Mechatronics Engineering as well. He then completed his Ph.D. at UMP specifically in the application of machine learning in aquaculture. His research interest includes optimization techniques, control systems, signal processing, instrumentation in aquaculture, sports engineering as well as machine learning. He is currently serving as a guest editor for SN Applied Sciences in a number of topical collections. He has also edited a number of volume in Springer's LNEE and AISC series. He is currently serving as the editor-in-chief for MEKATRONIKA: Journal of Mechatronics and Intelligent Manu
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Bibliographische Angaben
- 2023, 1st ed. 2022, XII, 580 Seiten, 276 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Ismail Mohd. Khairuddin, Muhammad Amirul Abdullah, Ahmad Fakhri Ab. Nasir, Jessnor Arif Mat Jizat, Mohd. Azraai Mohd. Razman, Ahmad Shahrizan Abdul Ghani, Muhammad Aizzat Zakaria, Wan Hasbullah Mohd. Isa, Anwar P. P. Abdul Majeed
- Verlag: Springer, Berlin
- ISBN-10: 9811920974
- ISBN-13: 9789811920974
Sprache:
Englisch
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