• Designed and implemented an ETL pipeline in Docker for processing and storing industrial data in a data lake and relational database.
• Integrated Solace as a message broker to optimize industrial data flow.
• Developed a monitoring system for hydraulic systems to detect anomalies and analyze operating cycles.

• Scaled predictive wear models across global mining sites using Azure ML Jobs for automated predictions.
• Optimized data preprocessing using SQL stored procedures for efficient ML training.
• Deployed retraining automation processes to continuously update models with historical machine data.

• Deployed ML models for daily wear prediction of primary crushers and cyclone pumps using Azure ML.
• Automated reporting systems to compare current machine states with historical performance data.

• Developed machine anomaly strategies based on historical failure analysis.
• Created Power BI dashboards and reports for monitoring and decision-making.
• Optimized SQL queries for faster data processing in maintenance analytics.

• Performed long-term analysis of equipment availability and operational patterns.
• Focused on primary crushers, conveyors, cyclone pumps, ball mills, and HPGR systems.

• Created structural calculation reports using simulation software like SAP2000, Inventor, Ansys Structural - Fluent and AutoCAD 3D.

• Optimized production processes using multiphysics CFD simulations with tools such as Ansys Structural, Fluent, Tekla, and Ametank.