A Machine Learning system to predict mining equipment failures before they happen. Built with XGBoost & Streamlit to minimize downtime and enhance safety.
Web application for selecting mining methods based on geological parameters, using methodologies like Nicholas 1981, 1992, UBC, and Sh&B. Supports quick technical and economic evaluations with geomechanical classification tools. Built with JavaScript, HTML5, and CSS3, without frameworks.
A web-based decision-support tool for mining engineers to evaluate and select underground access and ore transport systems (shaft, ramp & trucks, inclined belt conveyor). Built with Vue.js, Vuex, and Vue Router, the app uses three methodologies—Cardozo (2023), La Vergne (2003), and Moser (1996)—to guide early-phase decision-making.
Analytical Hierarchy Process Decision Tool is a web-based tool designed to facilitate decision-making across various domains using the Analytical Hierarchy Process (AHP). It allows users to define criteria and alternatives, perform pairwise comparisons with intuitive slider controls, and generate priority vectors for robust evaluation of options.
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