Last data update: Sep 16, 2024. (Total: 47680 publications since 2009)
Records 1-3 (of 3 Records) |
Query Trace: McNinch M [original query] |
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Leveraging IIoT to improve machine safety in the mining industry
McNinch M , Parks D , Jacksha R , Miller A . Min Metall Explor 2019 36 (4) [Epub ahead of print] 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. |
Intelligent monitoring system for improved worker safety during plant operation and maintenance
Parks D , McNinch M , Jacksha R , Nickerson H , Miller A . Min Eng 2019 71 (3) 34-38 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 U.S. 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 implementation of an IoT-based intelligent machine monitoring system to improve safety during operation and maintenance at a concrete batch plant. |
Mineworkers perceptions of mobile proximity detection systems
Bellanca JL , Swanson LR , Helton J , McNinch M . Min Metall Explor 2019 36 (4) 647-655 Accident data indicates that mobile haulage poses a significant pinning, crushing, and striking risk. Proximity detection systems (PDSs) have the potential to protect mineworkers from these risks. However, unintended consequences of mobile PDSs can undermine the safety benefit they provide. Soliciting iterative user input can improve the design process. Users help provide a critical understanding of how mobile PDSs may hinder normal operation and endanger mineworkers. Researchers explored users’ perspectives by conducting interviews with mineworkers from seven mines that have installed mobile PDSs on some of their haulage equipment. Mineworkers reported that mobile PDSs affect loading, tramming, section setup, maintenance, and general work on the section. Mineworkers discussed the operational effects and increased burden, exposure, and risk. Mineworkers also suggested that improved task compatibility, training, logistics, and PDS performance might help address some of these identified issues. This paper also gives additional insights into mobile PDS design and implementation. |
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