Mining Project: Evaluating and Developing Emerging Technologies to Improve Conveyor System Safety

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Principal Investigator
Start Date 10/1/2018
End Date 3/31/2023

To develop interventions to reduce traumatic injuries and fatalities that occur during operation and maintenance activities on conveyors.

Topic Areas

Research Summary

Fatalities and injuries to mine workers involving powered haulage continue to be a significant occupational health and safety burden. Mine Safety and Health Administration (MSHA) data clearly indicate an abnormally high number of injuries and fatalities due to operation and maintenance of conveyor systems, and this research was aimed at reducing such injuries and fatalities. Conveyor-related injuries and fatalities are a significant burden as indicated by MSHA releasing a Request for Information (RFI) in 2018 on safety improvements to mobile equipment and belt conveyors that included reference to such injuries. Specifically, the RFI stated that, “Since 2007, there have been 17 fatalities related to working near or around belt conveyors, of which 76 percent were related to miners becoming entangled in belt drives, belt rollers, and discharge points.”

To address these issues, this project had three research aims, which were carried out as described below.

  1. Increase situational awareness during operation and maintenance activities on conveyors and related stationary equipment. The focus was the design, building, and testing of an “intelligent monitoring system” for improving conveyor safety that incorporates emerging technologies and an Internet of Things (IoT) approach to monitoring and reporting a variety of safety parameters in real time. This system included a network of wireless sensors that collected data for analysis and presentation on mobile devices to monitor the status of maintenance activities, workers in hazardous locations, status and placement of machine guards, and lockout-tagout-testout (LOTOTO) status. The main focus was to develop the appropriate data integration, analysis, and presentation methodology that will have the greatest impact on improving worker situational awareness (SA). The system was tested using a laboratory setup that includes full-scale conveyors, and it was deployed in an active mine and evaluated for performance in collaboration with a mine operator. Software was written and evaluated to provide a user-friendly user interface that includes robust data storage methods and security. The system was used as a basis to study the impact of such technology on the SA of workers.  Challenges for this research included wireless coexistence and electromagnetic interference (EMI). This helped spawn a pilot project and full project for wireless coexistence, especially for safety critical systems.
  2. Improve worker safety around conveyors through the creation of automated maintenance and cleaning systems. This aim focused on identifying and exploiting opportunities to improve conveyor safety by using automation to obviate the manual tasks associated with conveyor spillage and cleanup. Information regarding the state of the art in this area was gathered by conducting a series of mine visits, targeting mines where multiple conveyors are in use. Hazardous maintenance tasks identified from accident data was targeted, and automated solutions that directly address those was sought and evaluated. Promising solutions were integrated along with the system described above and were refined based on feedback from NIOSH industry partners, with the goal of reducing accidents. Special attention was given to the issue of spillage and dust generation at conveyor transfer points, since this can cause overexposure to silica dusts. Interventions based on autonomous dust control were developed specifically to reduce silica exposure caused by transfer points.
  3. Develop concepts for Machine Situational Awareness (MSA) to enable equipment to actively monitor the surroundings for emergent hazards that could detrimentally affect miner health and/or safety. This aim focused on conveyor systems but would be ultimately applicable to all autonomous equipment operations. Recognition of this approach as being the best application of emerging technology on behalf of miner health and safety spawned a pilot project entitled Assured Autonomy Safety Intervention System Technology and a follow up proposal for MSA. Initial translational research was done to identify industry and academic approaches to critical components of MSA and evaluate their applicability and practicality for integration and introduction into the mining environment. Sensory and processing equipment was procured and assembled to begin the significant task of testing and evaluation of different approaches.

In summary, this project revealed that some technologies were not ready for implementation at mines and wireless co-existence vulnerabilities needed to be addressed for safety critical systems. The project also led the team to recognize that having equipment monitor the surroundings for hazards would augment human supervision significantly because machines to not suffer fatigue, loss of concentration, burnout, and other human lapses that ultimately allow hazards to evolve into injury. The conclusion was that additional research should be focused on taking full advantage of emerging technologies to create an MSA framework that could benefit all automated and autonomous equipment used in mining.

Related Publications

Jacksha R, Raj VK [2020]. Assessing the feasibility of a commercially available wireless internet of things system to improve conveyor safety. SME Annual Meeting, Phoenix AZ, February 23-26, Preprint #20-026, pp. 1-7. 

McNinch M, Parks D, Jacksha R, Miller A [2019]. Leveraging IIoT to improve machine safety in the mining industry. Mining, Metallurgy & Exploration 36(4):675-681.

Parks DA, McNinch MA, Miller AL, Jacksha RD [2019]. Intelligent monitoring system for improved worker safety during plant operation and maintenance. SME Annual Meeting, Denver, CO, February, 24-27, Preprint #19-033, pp 1-4.

Parks DA, McNinch MA, Miller AL, Jacksha RD [2019]. Intelligent monitoring system for improved worker safety during plant operation and maintenance. Mining Engineering 71(3). March.

Bissonette RH, Sbai S [2023]. Evaluation of models for interaction probability in autonomous monitor and control environments. SME Annual Meeting, Denver CO February 25-28, Presentation.

McNinch MA, Bissonette RH [2023]. Creating a framework for assured autonomy. SME Annual Meeting, Denver CO February 25-28, Presentation.

Bissonette RH, Sbai S [2023]. Evaluation of models for interaction probability in autonomous monitor and control environments. SME ApCom, Rapid City SD June 25-28, preprint 23-3226.

Page last reviewed: July 11, 2023
Page last updated: July 11, 2023