industrial-data

Intelligent analysis of industrial process data using neural networks, fuzzy clustering, ANFIS, and hybrid neuro-fuzzy models in MATLAB.

Dynamic system monitoring using HMM, BAFO and Monte Carlo

Public examples for Arclay's EU data APIs: Apify Actors, TED procurement, funding calls, product safety, industrial facilities, Python, pandas, DuckDB, and CRM imports.

Data Quality Assessment for Industrial Data

Enterprise Data Warehouse for Chocolate Manufacturing using SQL Server, ETL, Data Modeling, and Industrial Data Analytics.

ASNS (AI Sensory Neural System) is an evidence-first industrial AI architecture that structures identity, time, acquisition state, lineage, and replay before data enters databases.

Machine learning project to predict final steel temperature in industrial production processes.

Pipeline IIoT em tempo real com MQTT, Kafka, InfluxDB e Grafana — Cenário de Mineração

Reproducible Python workflow for simulating PLC-style machine operation data, fault events, anomaly labels, validation checks, and visual outputs.

A hands-on PostgreSQL dataset for learning Industrial SQL and Smart Factory analytics.

End-to-end industrial data pipeline built on Medallion architecture (Bronze / Silver / Gold) — SCADA ingestion, anomaly detection and Azure Blob Storage export

Classify SAP BOM components as plastic / polymer / rubber / non-plastic — rules + ML, with confidence, evidence, and a review queue for ambiguous or contradictory rows.

Process Engineering simulation tools for industrial efficiency, mass-balance calculations, and system purity optimization.

A from-zero, hands-on course through Cognite Data Fusion, the Cognite Toolkit, and one deliberately real industrial data model.

Controle de qualidade de dados industriais com Cognite Data Fusion (Open Industrial Data / plataforma Valhall): catálogo de 363 sensores, detecção de gaps, spikes, flatline e valores fora de faixa.

Reproducible Python pipeline for multi-machine manufacturing anomaly detection, automated testing and engineering reporting.

Modèle de maintenance prédictive basé sur un Random Forest optimisé pour détecter les pannes industrielles (AI4I 2020)

Perfil profissional: automação industrial, manutenção e dados industriais

Code and processed data accompanying the MSc thesis Integrating Dynamical Systems and Machine Learning for Modeling and Predicting Decay Across Wood Treatments, conducted at DTU in collaboration with the Danish Technological Institute.

Simulador de telemetria industrial SCADA/OT (Modbus TCP, sensores físico-químicos) com detecção de desvios e qualidade em Python/PostgreSQL.