Leveraging IIoT to Improve Machine Safety in the Mining Industry

Details

• Alternative Title:
  Min Metall Explor
• Personal Author:
  McNinch, M. ; Parks, D. ; Jacksha, R. ; Miller, A.
• Description:
  Each year, hundreds of mine workers are involved in machinery-related accidents. Many of these accidents involve inadequate or improper use of lockout/tagout (LOTO) procedures. To mitigate the occurrence of these accidents, new safety methods are needed to monitor access to hazardous areas around operating machinery, improve documentation/monitoring of maintenance that requires shutdown of the machinery, and prevent unexpected startup or movement during machine maintenance activities. The National Institute for Occupational Safety and Health (NIOSH) is currently researching the application of Internet of Things (IoT) technologies to provide intelligent machine monitoring as part of a comprehensive LOTO program. This paper introduces NIOSH's two phase implementation of an IoT-based intelligent machine monitoring system. Phase one is the installation of a proof-of-concept system at a concrete batch plant, while phase two involves scaling up the system to include additional sensors, more detailed safety/performance metrics, proximity detection, and predictive failure analysis.
• Subjects:
  Article Conveyor IoT Lockout/tagout Machine Safety
• Source:
  Min Metall Explor. 36(4):675-681
• Pubmed ID:
  33005876
• Pubmed Central ID:
  PMC7527258
• Document Type:
  Journal Article
• Funding:
  CC999999/ImCDC/Intramural CDC HHS/United States
• Volume:
  36
• Issue:
  4
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:f0bd1ca71f8ea48eb8f0a40c43a20ae6c6d1dea3175a2892107a14af0eb9739e
• Download URL:
  https://stacks.cdc.gov/view/cdc/94614/cdc_94614_DS1.pdf
• File Type:
  [PDF - 1013.22 KB ]