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Missouri University of Science and Technology

Mechanical Engineering

2018

Smart Manufacturing

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny Jun 2018

Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model …


Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin Jun 2018

Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In a smart manufacturing system involving workers, recognition of the worker's activity can be used for quantification and evaluation of the worker's performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband. The raw 10-channel IMU signals are stacked to form a signal image. This image is transformed into an activity image by applying Discrete Fourier Transformation (DFT) and then fed into a Convolutional Neural Network (CNN) for feature extraction, resulting in a high-level …