Masters Theses
Keywords and Phrases
Augmented reality; Deep learning; Internet of things; Machine learning; Mechanical assembly; Smart manufacturing
Abstract
"Quality and efficiency are pivotal indicators of a manufacturing company. Many companies are suffering from shortage of experienced workers across the production line to perform complex assembly tasks such as assembly of an aircraft engine. This could lead to a significant financial loss. In order to further reduce time and error in an assembly, a smart system consisting of multi-modal Augmented Reality (AR) instructions with the support of a deep learning network for tool detection is introduced. The multi-modal smart AR is designed to provide on-site information including various visual renderings with a fine-tuned Region-based Convolutional Neural Network, which is trained on a synthetic tool dataset. The dataset is generated using CAD models of tools augmented onto a 2D scene without the need of manually preparing real tool images. By implementing the system to mechanical assembly of a CNC carving machine, the result has shown that the system is not only able to correctly classify and localize the physical tools but also enables workers to successfully complete the given assembly tasks. With the proposed approaches, an efficiently customizable smart AR instructional system capable of sensing, characterizing the requirements, and enhancing worker's performance effectively has been built and demonstrated"--Abstract, page iii.
Advisor(s)
Leu, M. C. (Ming-Chuan)
Committee Member(s)
Yin, Zhaozheng
Qin, Ruwen
Department(s)
Mechanical and Aerospace Engineering
Degree Name
M.S. in Manufacturing Engineering
Sponsor(s)
National Science Foundation (U.S. )
Missouri University of Science and Technology Intelligent Systems Center
Research Center/Lab(s)
Intelligent Systems Center
Publisher
Missouri University of Science and Technology
Publication Date
Fall 2018
Pagination
ix, 52 pages
Note about bibliography
Includes bibliographical references (pages 48-51).
Rights
© 2018 Ze-Hao Lai, All rights reserved.
Document Type
Thesis - Open Access
File Type
text
Language
English
Thesis Number
T 11428
Electronic OCLC #
1084478847
Recommended Citation
Lai, Ze-Hao, "Smart augmented reality instructional system for mechanical assembly" (2018). Masters Theses. 7827.
https://scholarsmine.mst.edu/masters_theses/7827
Comments
The author acknowledges and thanks all the funding sources granted from National Science Foundation CMMI-1646162 and the Intelligent Systems Center at Missouri University of Science and Technology.