Activity-Based Respirable Dust Prediction in Underground Mines Using Artificial Neural Network

Details

• Personal Author:
  Amoako R ; Brickey A
• Description:
  Production activities in underground mines generate respirable dust which impacts worker's health and productivity. This underscores the importance of accurately predicting dust concentration towards effecting proactive and timely measures of mitigation. We develop an artificial neural network (ANN) model for an underground metal mine that predicts dust concentration using input parameters that are derived from production activities. The model provides fairly good results, with the prospect of yielding better results with improved data collection. The model produces a correlation of 0.70 between the predicted and actual dust concentration. The work in this paper constitutes the first phase of a larger framework that seeks to manage workers' exposure to respirable dust by incorporating ventilation in short-term production scheduling. In a future work, we seek to incorporate predictions from the ANN model and the impact of conventional dust controls into short-term production schedule optimization as mathematical constraints. This will aid in identifying high dust production activities proactively, and effectively managing available ventilation and dust control measures to enhance miners' safety. Description provided by NIOSH
• Subjects:
  • Air Pollutants, Occupational
  • Air Pollution
  • Dust
  • Mining
  • Occupational Health
  • Particulate Matter
  • Safety
  • Ventilation
• Keywords:
  • Mining industry
  • Underground mining
  • Ventilation
  • Neural networks
  • Mine workers
  • Air quality control
  • Airborne particulates
  • Respirable dust
  • Models
  • Dust control
• ISBN:
  9781032036793
• Document Type:
  Text
• Funding:
  Contract
• Editor:
  Tukkaraja P
• Genre:
  Proceedings
• Place as Subject:
  OSHA Region 8 ; South Dakota
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  410-418
• NIOSHTIC Number:
  nn:20063606
• Citation:
  Mine Ventilation: Proceedings of the 18th North American Mine Ventilation Symposium (NAMVS 2021), June 12-17, 2021, Rapid City, South Dakota. Tukkaraja P ed. London: CRC Press, 2021 Jun; :410-418
• Editor(s):
  Tukkaraja P
• Federal Fiscal Year:
  2021
• Performing Organization:
  South Dakota School of Mines and Technology
• Peer Reviewed:
  False
• Source Full Name:
  Mine Ventilation: Proceedings of the 18th North American Mine Ventilation Symposium (NAMVS 2021), June 12-17, 2021, Rapid City, South Dakota
• Download URL:
  https://stacks.cdc.gov/view/cdc/222181/cdc_222181_DS1.pdf
• File Type:
  [PDF - 462.60 KB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:925fe035a99944b7be9fec06c7088786be210ef7ef18d3a9f39971fdf82a15ec5e3a0994adc1486773ce0fd73ab8b7c92c74d911c3b77dd2b3229f70ce54ff94