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Titlebook: Enabling Industry 4.0 through Advances in Mechatronics; Selected Articles fr Ismail Mohd. Khairuddin,Muhammad Amirul Abdullah,A Conference

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发表于 2025-3-21 16:10:16 | 显示全部楼层 |阅读模式
书目名称Enabling Industry 4.0 through Advances in Mechatronics
副标题Selected Articles fr
编辑Ismail Mohd. Khairuddin,Muhammad Amirul Abdullah,A
视频video
概述Presents selected articles from the mechatronics track of the iM3F 2021 conference, Malaysia.Highlights recent findings in mechatronics pertinent toward the realization and embodiment of Industry 4.0.
丛书名称Lecture Notes in Electrical Engineering
图书封面Titlebook: Enabling Industry 4.0 through Advances in Mechatronics; Selected Articles fr Ismail Mohd. Khairuddin,Muhammad Amirul Abdullah,A Conference
描述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.
出版日期Conference proceedings 2022
关键词Robotic vision; Autonomous mobile robots; Motion control; Intelligent sensors and actuators; Industrial
版次1
doihttps://doi.org/10.1007/978-981-19-2095-0
isbn_softcover978-981-19-2097-4
isbn_ebook978-981-19-2095-0Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Venkat Reddy Konasani,Shailendra Kadreic measures. Outcomes from the questionnaires demonstrate that the participants experience higher anxiety and higher reactance in stress condition than in relax condition. A future study might include other physiological signals for attaining robust classifications in developing a better stress dete
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https://doi.org/10.1007/978-1-4842-1769-6he system which are data acquisition, data pre-processing, data training and data testing. In this study, an improved classification algorithm using deep learning specifically convolutional neural network is used to detect the lane markers. The big dataset consists of 5000 images. It is distributed
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https://doi.org/10.1007/978-1-4842-3057-2 maximum deformation of 1.015e.m and a generated Von-Mises stress of 4.827e .N/m.. Other than that, 2.5227e. N/m. of Von-Mises stress is obtained in the impact frontal test. With a great impact of cruising at a speed of 15.6464 m/s, 5.6053e. m deformation is obtained in the same test. As a result, t
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https://doi.org/10.1007/978-1-4842-7407-1r sizing calculation is used to obtain the motor‘s power, speed, and torque based on some parameters required by user limitation. Simulation is performed using MATLAB R2020b Simulink to model and analyze the three wheels electric scooter’s performance. BLDC motor with 800 W power, 1000 rpm speed and
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