workflow type). This methodology ensures that results are grounded in operational data, providing a replicable framework for assessing MDM implementations in underground mining contexts. 4. IMPLEMENTATION (DESWIK MDM) The implementation of Deswik MDM (Mining Data Management) at Aripuanã was executed over a six-month period, from early 2024-Q4 to mid-2025-Q1, involving close collaboration with Deswik's technical team. The process began with a diagnostic phase to map existing data flows and identify fragmentation points, followed by platform configuration, workflow development, and user training. Training sessions were conducted both in-person and remotely, ensuring comprehensive coverage for the 80+ users across six technical disciplines: short-, medium-, and long-term mine planning, geology, geomechanics, topography, ventilation, and mine infrastructure. The timeline emphasized iterative testing and feedback loops to align workflows with operational realities. Data mapping and standardization formed the foundation of the implementation. Operational data sources—including geological models, topographic surveys, geomechanical assessments, ventilation designs, and infrastructure layouts—were ingested into Deswik MDM through automated connectors and manual uploads. Standardization focused on naming conventions, data schemas, and metadata tagging to eliminate ambiguities. For instance, topographic files were restructured from multiple uncontrolled versions in shared repositories to a single, version-controlled format, with automatic timestamping and audit trails. Over 40 standardized workflows were deployed, categorized by discipline and function. These workflows automated routine processes, enforced validation mechanisms, and ensured traceability. Key categories included: (i) topographic data management (e.g., survey ingestion and version control); (ii) planning reconciliation (e.g., stoping block updates and sequencing); (iii) geological and geomechanical validation (e.g., model updates with risk assessments); (iv) ventilation and infrastructure monitoring (e.g., design approvals and status tracking); and (v) crossdisciplinary integration (e.g., multidisciplinary validation gates for project releases). Each workflow incorporated conditional logic for error detection, such as flagging inconsistencies in tonnage estimates or excavation sequences, and required approvals from relevant stewards before outputs were released. Quality controls were embedded throughout the platform, including automated validation rules (e.g., range checks for grade data, geometric consistency for designs) and manual review gates for high-risk deliverables. Version control ensured that only the latest approved files were accessible, with historical versions archived for audit purposes. Integration with Business Intelligence tools, such as Power BI, enabled real-time dashboards for monitoring workflow performance and operational indicators. The implementation timeline, as illustrated in the project schedule, highlighted phased rollouts by discipline, with Deswik's team providing ongoing support to address technical challenges and optimize user adoption.
RkJQdWJsaXNoZXIy MTM0Mzk2