IL3.3C - Processes Reconstruction for Workflow Analysis and Bottleneck Detection

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.

  • Main Gain(s): Product-design decision support, Forecast visualization, Model ranking, News-enriched analytics

  • Use Case(s): Technical users in product-design teams using product dashboards, forecasts and real Bosch data feeds

  • Start TRL: TRL 4

  • Final TRL: TRL 7

  • 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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    <th class="px-3 py-3 text-center font-semibold">Control Tower Integration</th>
    <th class="px-3 py-3 text-center font-semibold">REST API</th>
    <th class="px-3 py-3 text-center font-semibold">Containerized Application</th>
    <th class="px-3 py-3 text-center font-semibold">Extensible</th>
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      Product Capabilities
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      <span class="inline-flex h-6 w-6 items-center justify-center rounded-full bg-emerald-100 text-emerald-700">✓</span>
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  • 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