Abstract
This paper outlines the results of an experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance (or work instructions) of highly customised and high-risk manual operations. The focus is on human operators’ training effectiveness and performance and the aim is to test if such technologies can support enhancing the knowledge retention levels and accuracy of task execution to improve health and safety (H&S). A new
AR enhanced assembly method is proposed and experimentally tested using a real industrial process as case study for electric vehicles’ (EV) battery module assembly. The experimental results revealed that the proposed method improved the training practices and performance through increases in the knowledge retention levels from 40% to 84%, and accuracy of task execution from 20% to 71%, when compared to the traditional paper-based method. The results of this research validate and demonstrate how emerging technologies are advancing the choice for manual, hybrid or fully automated processes by
promoting the XR-assisted processes, and the connected worker (a vision for Industry 4 and 5.0), and supporting manufacturing become more resilient in times of constant market changes.
AR enhanced assembly method is proposed and experimentally tested using a real industrial process as case study for electric vehicles’ (EV) battery module assembly. The experimental results revealed that the proposed method improved the training practices and performance through increases in the knowledge retention levels from 40% to 84%, and accuracy of task execution from 20% to 71%, when compared to the traditional paper-based method. The results of this research validate and demonstrate how emerging technologies are advancing the choice for manual, hybrid or fully automated processes by
promoting the XR-assisted processes, and the connected worker (a vision for Industry 4 and 5.0), and supporting manufacturing become more resilient in times of constant market changes.
Original language | English |
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Title of host publication | 16th International Conference on Computers and Industrial Engineering (ICCIE 2022) |
Publisher | World Academy of Science, Engineering and Technology |
Pages | 56-60 |
Number of pages | 5 |
Publication status | Published - 2 Jun 2022 |
Event | 16th International Conference on Computers and Industrial Engineering - San Francisco , United States Duration: 2 Jun 2022 → 3 Jun 2022 |
Publication series
Name | World academy of science, engineering and technology |
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ISSN (Electronic) | 1307-6892 |
Conference
Conference | 16th International Conference on Computers and Industrial Engineering |
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Abbreviated title | ICCIE 2022 |
Country/Territory | United States |
City | San Francisco |
Period | 2/06/22 → 3/06/22 |