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.
Machine learning project to predict final steel temperature in industrial production processes.
Collects MCEGold measurement publications and performs publication-driven discovery for industrial asset reliability applications.
A hands-on PostgreSQL dataset for learning Industrial SQL and Smart Factory analytics.
Reproducible Python workflow for simulating PLC-style machine operation data, fault events, anomaly labels, validation checks, and visual outputs.
Veritag: Manufacturing Knowledge Hub for chemical plants. Answers with evidence, finds failure lessons that did not travel, and keeps engineers in control. CALIBER 2026 Case 1 prototype by Team Anti Hero Department, Universitas Diponegoro.
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.
Open-source discovery and visualization platform demonstrating MCEGold Data Services integration through a web portal, automated publication collection, and Grafana.
Gas turbine sensor monitoring: Python + PostgreSQL, time-series queries and anomaly detection.
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.
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.
Evidence-preserving industrial PDF extraction with NVIDIA VLMs, validated product records, citation-bearing RAG, and a deterministic offline demo.
Reproducible Python pipeline for multi-machine manufacturing anomaly detection, automated testing and engineering reporting.
To associate your repository with the industrial-data topic, visit your repo's landing page and select "manage topics."