Authors: Wessels, SDN; Dixon, R

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Wessels, SDN & Dixon, R 2020, 'Geotechnical data aggregation and visualisation supporting informed risk management: the one-stop geotech shop', in PM Dight (ed.), Slope Stability 2020: Proceedings of the 2020 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering, Australian Centre for Geomechanics, Perth, pp. 703-712,

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Rio Tinto Iron Ore (RTIO) operates 16 mine operations in the Pilbara region of Western Australia. At each operation, there could be many active pits that pose a challenge for the effective management of geotechnical risks with limited resources. There are many information sources which the geotechnical engineer uses for risk management, including temporal and non-temporal data that may or may not be georeferenced. This information can be in various places, such as proprietary software, network servers or local devices. Consolidating this information can be time-consuming for the engineer and may not include all available data sources. To address this, RTIO developed an in-house tool for aggregating and visualising data, where all geotechnical data can be accessed in a single platform and also included a dashboard to provide visibility of monitoring status and risk profiles across all RTIO Pilbara operations. Sustainability of an in-house developed tool poses business challenges and a decision was made to explore available external options. Although a number of off-the-shelf applications were identified, none met all the RTIO requirements. The best-fit application was ultimately selected with RTIO working with the vendor to incorporate all defined software requirements. This paper discusses RTIO expectations and requirements for the data aggregation and visualisation application, challenges relating to the in-house system development, the evaluation process for a vendor managed option and development of the application functionality with the selected vendor.

Keywords: geotechnical risk management, slope monitoring, data aggregation, visualisation, multi-pit operations

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