Evaluation of a Collision Avoidance System at an Underground Mine

M. Chinavaenzwa, M. Munsamy, J. H. Pretorius

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publication2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1593-1597
Number of pages5
ISBN (Electronic)9798350323153
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 - Singapore, Singapore
Duration: 18 Dec 202321 Dec 2023

Publication series

Name2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023

Conference

Conference2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
Country/TerritorySingapore
CitySingapore
Period18/12/2321/12/23

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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