Abstract
Collision avoidance system's design and configuration introduce operational delays, particularly in mines where several mobile machines and workers interact. Following the deployment of a radio-frequency identification collision avoidance system on underground loaders at a platinum mine in South Africa, production decreased by 13.28%. This research study focusses on determining the system's impact on productivity, its constraints, ranging and detection accuracy. By triggering alarms and measuring activation distances for stop, crawl and caution mode the system was assessed on surface and underground in static and dynamic trials. Caution mode was the most accurate and crawl mode the least, rear direction was the safest and front was least safe, the system performed better underground than on surface. Metallic parts of the loader which were in line of measurement, caused tag detection failure in front of the bucket during surface trials, and distortion in distance estimation which influenced productivity. Utilising Received Signal Strength technology rather than Return Time of Flight may improve the system's accuracy because of its even magnetic field distribution in the presence of metallic objects.
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1593-1597 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350323153 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 - Singapore, Singapore Duration: 18 Dec 2023 → 21 Dec 2023 |
Publication series
| Name | 2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 |
|---|
Conference
| Conference | 2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 |
|---|---|
| Country/Territory | Singapore |
| City | Singapore |
| Period | 18/12/23 → 21/12/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Collision avoidance system
- loader
- radio-frequency identification
- tag
- underground mine
ASJC Scopus subject areas
- Artificial Intelligence
- Decision Sciences (miscellaneous)
- Statistics, Probability and Uncertainty
- Industrial and Manufacturing Engineering
- Modeling and Simulation
- Strategy and Management
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