Mining Project: Emerging Technologies to Improve Conveyor System Safety

Principal Investigator
Start Date 10/1/2018

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 proposed research is aimed at reducing such injuries and fatalities. Conveyor-related injuries and fatalities are a significant burden as indicated by MSHA recently releasing a Request for Information (RFI) 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 has four research aims, which will be carried out as described below.

  1. Increase situational awareness during operation and maintenance activities on conveyors and related stationary equipment. The initial focus will be 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 will include a network of wireless sensors that collect 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 will be to develop the appropriate data integration, analysis, and presentation methodology that will have the greatest impact on improving worker situational awareness (SA). The system will be tested using a laboratory setup that includes full-scale conveyors, and will also be deployed in an active mine and evaluated for performance in collaboration with a mine operator. Software will be developed and/or evaluated to provide a user-friendly user interface that includes robust data storage methods and security. When the system is complete, it will be used as a basis to study the impact of such technology on the SA of workers. As workers will be provided with a range of real-time data (status of LOTOTO, safeguards, and equipment) through a mobile device, researchers will determine the degree to which SA is improved through this information.
  2. Reduce catastrophic conveyor failures and worker exposure to hazards through real-time data and a predictive failure mode analysis. This aim utilizes the data from the system of research aim 1 to prevent hazardous situations from occurring due to undetected equipment failures. Research will include identifying conveyor failure modes and the specific components that may contribute to failures. Sensors will be chosen to collect the pertinent data, and software will be developed to process the data in a manner that can help predict failures. Research will include the evaluation of drones for collecting large data sets from multiple sensors as a way of improving failure analysis by using large data sets. The failure analysis software will be tested and evaluated in collaboration with an active mine, and feedback will be used to improve performance.
  3. Improve worker safety around conveyors through the creation of automated maintenance and cleaning systems. This aim focuses 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 will be gathered by conducting a series of mine visits, targeting mines where multiple conveyors are in use. Hazardous maintenance tasks identified from accident data will be targeted, and automated solutions that directly address those will be sought and evaluated. Promising solutions will be integrated along with the system described above, and refined based on feedback from NIOSH industry partners, with the goal of reducing accidents. Special attention will be payed 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 will be developed specifically to reduce silica exposure caused by transfer points.
  4. Develop improved training materials and protocols to address the role of human factors in preventing injuries and increase machine safety awareness. This aim will focus on the human factors associated with conveyor accidents, and will address worker needs via effective training. New training content will be developed to target gaps in current conveyor safety training, and may take the form of internet videos, tailgate modules, or best practice guides. Training may also include developing tools that can be used by operators to comply with the new MSHA regulation on pre-shift inspections. That approach will include collaboration with MSHA to identify the best format for such tools, with focus on the potential development of a mobile app that can be easily modified by mine personnel to fit their needs.

This research will help eliminate injuries and fatalities related to worker-machine interactions by reducing exposures to hazardous conditions in mining environments. The work will result in tangible products as well as guidance and best practices for implementing intelligent monitoring systems related to machine safety. The field demonstration of new products, such as electronic maintenance planning centers and software interfaces that allow easy access to machine safety information via mobile devices, will improve LOTOTO procedures and increase situational awareness, thus reducing maintenance-related accidents. Human factors and behavioral studies will help to elucidate root causes and identify interventions to prevent worker entanglement and other injuries related to working on or near conveyors. Finally, training materials that are developed will improve the overall safety of maintenance procedures. The desired outcomes of the research are that the mine operators will adopt new technologies and methods that reduce the injuries and fatalities associated with operation and maintenance of conveyor systems 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.

Page last reviewed: 4/16/2020 Page last updated: 2/19/2019