A functional automated Exploratory Data Analysis system for Bosch heat-pump manufacturing data. It integrates AutoML, local LLM-based metadata enrichment, an ML Readiness metric and FAIR data-maturity reporting, and was tested with real Nexeed MES datasets from Bosch.
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Main Gain(s): Automated exploratory analysis, Improved FAIR data maturity, ML readiness assessment, Persistent reporting for industrial datasets
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Use Case(s): Real Nexeed MES datasets from Bosch Termotecnologia heat-pump production processes
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Start TRL: TRL 3
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Final TRL: TRL 6
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Main Contributions: Universidade de Aveiro (coord. Prof. Eugénio Rocha; support Diogo Costa) with Bosch Termotecnologia, S.A. (coord. Eng. Nelson Ferreira)
Main Features
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Product Capabilities
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- Automated exploratory and descriptive-statistics reports for high-volume batch data
- Local Large Language Models for dataset descriptions and metadata enrichment
- AutoML functionality to assess predictive potential in industrial datasets
- ML Readiness metric for objective data-science readiness assessment
- Dataverse-based FAIR framework with persistent reporting
- Integration into the Project 3 Control Tower