pedrolbacelar / Digital_Twin

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[DigiMind] Dividir tasks and report very clear #261

Closed pedrolbacelar closed 1 year ago

pedrolbacelar commented 1 year ago
  1. Executive Summary (ANDREA)
    1. One page document describing the scope of the project
    2. Importance of the application field (industry 4.0 and RCT)
    3. Brief about the solution (specially highlight the value created)
  2. Introduction (ANDREA)
    1. Team presentation
    2. Mentioning the interview?
    3. MindSphre challenge brief
    4. Context of the project (industry 4.0, RCT, IoT, they talked a lot about this in the presentations)
    5. MindSphre understanding (what is mindsphere, what is it relevant?)
  3. DigiMind Glimpse… (ANDREA)
    1. 2 to 3 pages explaining in generical terms DigiMind
    2. What is DigiMind?
    3. Why DigiMind?
    4. How it Works?
  4. Methodology (ANDREA)
    1. Timeline of the project (phases, we talk a lot about this on the interview)
      1. Problem discovery
      2. Ideation
      3. Development
    2. Idea Challenge outcome
    3. Team Structure
      1. How the team was structure in different phases (they asked this in the interview)
      2. WIP frontend, backend (machine learning), business
  5. The Business (ANDREA)
    1. Benchmarking of competitors
    2. Personas
    3. Stakeholder
    4. Value Proposition Canvas
      1. benefits
      2. pain release
    5. Business Model Canvas
  6. The Technology
    1. General framework overview and explanaition of main features
      1. Frontend (Dashboard)
      2. API interface
      3. Backend (Maching Learning)
    2. Frontend detail explanation
      1. Assets and Aspects overview (MindSphre Features)
      2. Detail explanation of the flow chart of the dashboard
      3. API functions explanation
    3. Backend detail explanation
      1. Simulator?
        1. Model layout
        2. Model components
        3. Model Translation
        4. Model Run
        5. RCT calculation
      2. Database generator
        1. different approaches
      3. Machine Learning Training
        1. Pipeline
      4. Machine Learning Prediction
  7. Use Case
    1. Lego Factory
      1. What is it?
      2. Physical structure
        1. Station
        2. Queue
        3. Closed Loop scope
    2. Test with physical system data
    3. Graph and Results
  8. Demo & Step by Step (User Guide)
    1. Download the library
    2. How to create a model and run a simulation
    3. How to train the database
    4. How to predict the RCT using the trained model
  9. Next Steps & Further comments
    1. Conclusion
    2. Acknowledgment
  10. Appendix
    1. Frameworks details
    2. Assumptions
    3. Extra pictures