Track 1: AI and Data-Driven Decision Making

also restores technological independence to the mining company's procurement and engineering teams. Measurable Operational Resilience: The transition to a Cloud-Agnostic infrastructure, coupled with the deployment of a centralized Geotechnical Command Center, yielded transformative results. The case study recorded a dramatic increase in real-time data availability jumping from historical averages of ~65% to over 95%. Furthermore, reporting efficiencies evolved from requiring days of manual compilation to near-instantaneous automated generation, drastically reducing the cognitive load on engineering staff. Proactive Risk Management (TARP Automation): Moving away from isolated sensor analysis, the algorithmic spatial grouping of instruments proved highly effective in reducing false alarms. By automating TARP thresholds within geotechnically homogeneous zones, the platform successfully shifted the operational paradigm from a reactive "Run-to-Failure" approach to a predictive, early-warning strategy. Ultimately, technology alone cannot prevent geotechnical failures, but isolated data guarantees poor decision-making. By prioritizing interoperability, data sovereignty, and intuitive visualization, the proposed INGETEC DATA framework empowers stakeholders at all levels from field analysts to board executives to make rapid, risk-informed decisions. This digital ecosystem provides the necessary foundation to ensure asset integrity, fulfilling the ultimate industry objective: delivering minerals in a smarter, safer, and more responsible way. ACKNOWLEDGEMENTS The authors gratefully acknowledge the mining operation in Peru for providing operational context and data access for the case study. The views and framework presented in this paper are those of the authors and do not necessarily represent those of any technology vendor or mining company. REFERENCES ANCOLD (2019). Guidelines on Tailings Dams – Planning, Design, Construction, Operation and Closure, Revision 1. Australian National Committee on Large Dams. Barnewold, L., & Lottermoser, B.G. (2020). Identification of digital technologies and digitalisation trends in the mining industry. International Journal of Mining Science and Technology, 30(5), 747–757. DOI: 10.1016/j.ijmst.2020.07.003. Canadian Dam Association (CDA) (2013). Dam Safety Guidelines (revised 2013). Ottawa, Canada. GISTM (2020). Global Industry Standard on Tailings Management. International Council on Mining and Metals (ICMM), United Nations Environment Programme (UNEP), Principles for Responsible Investment (PRI). ICMM (2025). Tailings Management Good Practice Guide. International Council on Mining and Metals, London. ICOLD (2013). Bulletin 158: Dam Surveillance Guide. International Commission on Large Dams, Paris.

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