Robotic 3D printing monitoring
Objective:
Development of a sensor-based solution for real-time monitoring and data collection in large-scale FGF printing. The system will include temperature, pressure, torque sensors, and vision technology.
Enhancement of the energy efficiency and optimization of the printing process.
Creation of predictive models to improve process control using the collected data.
Expected Working Principle:
- Enhancing large-scale 3D printing requires better material behavior insights and process control.
- Real-time temperature and pressure sensors can improve interlayer adhesion and product stability.
- Lab tests like Melt Flow Rate (MFR) and Differential Scanning Calorimetry (DSC) help optimize printing parameters.
- Continuous scanning and energy monitoring can detect defects early and improve efficiency.
- A control system will interpret sensor data to adjust printing settings in real-time for better product quality.
Initial Solutions to be Investigated:
Sensoring System for "First Time Right" Printing:
- Modeling energy consumption in extrusion and analysis processes
- Initial testing with FDM (Fused Deposition Modeling)
- Scaling up for FGF printing
Upscaling Printing Capabilities:
- Implementation of advanced sensor networks for larger-scale production
Material Recycling and Predictive Modeling:
- Investigating material properties and recycling options, alongside predictive models to optimize print quality and process efficiency.
