Predictive maintenance system that analyzes industrial sensor data to estimate machine failure risk and visualize equipment health through a FastAPI and React dashboard.

Complete data architecture and machine learning project for industrial cost analysis. Includes a modern ETL pipeline (Bronze-Silver-Gold), validations with Great Expectations, Prefect orchestration, in-depth EDA, predictive models (Random Forest and Gradient Boosting), and deployment via Streamlit.

End-to-end predictive maintenance project on the AI4I 2020 dataset. Includes feature engineering, calibrated logistic regression and random forest pipelines, with attention to class imbalance and operating-point evaluation (PR-AUC, recall @ 90% precision).

This repo is a fork of https://github.com/grafana/grafana as used by Empolis Information Management GmbH as part of Empolis Service Express Industrial Analytics.

PSistema de monitoreo predictivo para enfriadores de ácido sulfúrico (CAP-3), basado en ingeniería térmica, análisis de ensuciamiento, evaluación de criticidad y machine learning supervisado.

Локальные управленческие дашборды для проверки сценариев на Excel/CSV-выгрузках

Production-grade Oil & Gas Operational Reliability & Predictive Maintenance Intelligence Platform | 9-page Streamlit dashboard | ROC-AUC 0.9381 | ISO 14224 | Python · ML · Docker

AM L and web application for classifying industrial chemical production batches into operational performance clusters using K-Means clustering. Flask REST API backend and React + Vite frontend with real-time batch classification.

UniversityHack 2024 challenge solution focused on lot-level industrial analytics and predictive modeling.

Python CLI concept for parsing raw manufacturing machine logs into structured CSV data for industrial analysis, reporting, and future predictive maintenance workflows.

ML model forecasting gold recovery rates from ore processing. Identifies unprofitable production runs by analyzing flotation parameters and metal concentrations at rougher and final stages, enabling mining companies to optimize resource allocation and improve extraction efficiency.

中国石油大学（华东）工程概论课程作业-对计算机领域复杂工程问题进行案例分析-三维计算机图形软件的设计与开发

Sistema digital predictivo para el monitoreo térmico de intercambiadores EP-101 en Planta de Ácido (Chuquicamata), basado en Python, Streamlit y analítica avanzada para mantenimiento predictivo.

Exactspace Data Science Take-Home Assignment: Industrial sensor analytics, clustering, anomaly detection, forecasting, and a retrieval-augmented generation (RAG) LLM prototype – by Gunal D (BTech CSE, Bangalore).

Engineering analysis, digital twin development, and industrial analytics for heat exchanger fouling assessment.

Industrial Power BI dashboard for monitoring OEE, Production Volume, Downtime, Yield Rate and Defects.

Machine learning pipeline for predicting industrial gold recovery, optimizing process efficiency using sMAPE and ensemble regression models.

Chairperson Award — 1st Position · Python + HTML/CSS · Automated PI/DCS data extraction, real-time & historical trend analysis, equipment health monitoring & one-click DSM report generation · Zero manual DCS entry · Jindal Power Limited

Operational Health Scoring for industrial process monitoring, anomaly detection and contextual analytics.

HSE Incident Analytics & Process Safety Intelligence Platform | API RP 754 · ISO 45001 · NUPRC | 8-page Streamlit dashboard | Oil & Gas | Python · SQLite · Docker