IL3.3B - Repair Recommendation API
A Python web application supporting product-design teams through product dashboards, forecasts and model rankings. It includes news-based time-series enrichment using local LLaMA extraction and sentiment analysis, and is integrated with the Control Tower and real data feeds.
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Main Gain(s): Product-design decision support, Forecast visualization, Model ranking, News-enriched analytics
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Core Contributions: Universidade de Aveiro (coord. Prof. Eugénio Rocha; support Diogo Costa) with Bosch Termotecnologia, S.A. (coord. Eng. Nelson Ferreira)
Use Cases:
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Technical users in product-design teams using product dashboards, forecasts and real Bosch data feeds
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Start TRL: TRL 2
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Final TRL: TRL 5
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Main Features
- Python web application with dashboards for products, forecasts and model rankings
- Refined interface for non-specialist technical users
- Automatic extraction and summarization of relevant news using a local LLaMA workflow
- Sentiment-analysis features for time-series enrichment
- Integration into the Project 3 Control Tower
- Feeding from real data via API