industrial-data

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

Data Quality Assessment for Industrial Data

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.

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

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

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

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

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

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.

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

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

Synthetic NLP workflow for structuring industrial standardization and commercialization demands for turquoise-hydrogen-derived carbon materials.

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.

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