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Enabling Industry 4.0 through Advances in Mechatronics
Selected Articles from iM3F 2021, Malaysia
eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9789811920950
Veröffentl:
2022
Einband:
eBook
Seiten:
580
Autor:
Ismail Mohd. Khairuddin
Serie:
900, Lecture Notes in Electrical Engineering
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:
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.
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.
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.