Periodic Reporting for period 2 - FLASH-COMP (Flawless and sustainable production of composite parts through a human centred digital approach)
Reporting period: 2024-04-01 to 2025-03-31
The FLASH-COMP project aims to develop a fast and reliable (FLASH) human-oriented quality control solution capable of identifying in a timely-manner effectiveness during Liquid Resin Infusion (LRI) composites manufacturing process and consequently, to determine the in-situ corrective actions to be implemented, towards zero-defects manufacturing, significantly reducing the generation of polymer composites waste.
FLASH-COMP idea is to employ novel, fast and accurate Inspection and Monitoring techniques (FLASH-IM) within the most critical manufacturing stages – pre-forming and infusion, to retrieve key process parameters. This data will feed an AI-based Defect Severity Estimation Tool (FLASH-DSET), capable of estimating the generation of defects and, in consequence, determining if and what kind of corrective actions should be adopted within the pre-forming and resin infusion operations. Instructions will be linked to real-time feedforward and feedback (FF/FB) control strategy Decision Support System (FLASH-DSS) which will allow workers to take instant and precise corrective actions paving the way towards first-time-right manufacturing.
The smart knowledge will be fed from interoperable and sovereign data sharing between sites and factories. In this way, the composite sector will take advantage of the latest technological innovations to digitalise manufacturing processes towards a more sustainable and competitive composite industry.
FLASH-COMP idea is to employ novel, fast and accurate Inspection and Monitoring techniques (FLASH-IM) within the most critical manufacturing stages – pre-forming and infusion, to retrieve key process parameters. This data will feed an AI-based Defect Severity Estimation Tool (FLASH-DSET), capable of estimating the generation of defects and, in consequence, determining if and what kind of corrective actions should be adopted within the pre-forming and resin infusion operations. Instructions will be linked to real-time feedforward and feedback (FF/FB) control strategy Decision Support System (FLASH-DSS) which will allow workers to take instant and precise corrective actions paving the way towards first-time-right manufacturing.
The smart knowledge will be fed from interoperable and sovereign data sharing between sites and factories. In this way, the composite sector will take advantage of the latest technological innovations to digitalise manufacturing processes towards a more sustainable and competitive composite industry.
FLASH Simulations: AI & Physics Driven Digital Hybrid Twin™ Platform
Reduced Order Model (MOR) simulation for curing was validated for industry specyfic materials and geometries. Model was deployed on digital data space, allowing live integration with sensors.
Near real time hybrid infusion simulation (with sub-calibration of permeability done on the fly) was developed and demonstrated on test bed.
Hybrid Twin for virtual assessment of part performance was established and tested at Azimut case geometry.
Fully functional operator dashboard was created, supporting evolving toolsets and system components.
Test Bed Ecosystem and Digital-Physical Data Interoperability
Digital infrastructure deployment completed, with microservice-based architecture implemented and data management and communication tools integrated.
Simulation and control features enabled (e.g. ESI cure degree simulation, infusion simulation integrated with front flow monitoring).
All inspection and monitoring tools integrated together and tested at test bed facility (TRL6).
Further adjustments of LiDAR and FOS technology done to ensure scalability for large parts and usability in day-to-day manufacturing operations.
Economic, Green & Waste Assessment Framework
Development of the ZDM maturity model and its online assessment questionnaire.
Carrying out the first level ZDM maturity assessment as well as Eco-efficiency assessment of the industrial use-cases.
Dissemination of the developed ZDM maturity model within the ZDM cluster and at international conferences.
Reduced Order Model (MOR) simulation for curing was validated for industry specyfic materials and geometries. Model was deployed on digital data space, allowing live integration with sensors.
Near real time hybrid infusion simulation (with sub-calibration of permeability done on the fly) was developed and demonstrated on test bed.
Hybrid Twin for virtual assessment of part performance was established and tested at Azimut case geometry.
Fully functional operator dashboard was created, supporting evolving toolsets and system components.
Test Bed Ecosystem and Digital-Physical Data Interoperability
Digital infrastructure deployment completed, with microservice-based architecture implemented and data management and communication tools integrated.
Simulation and control features enabled (e.g. ESI cure degree simulation, infusion simulation integrated with front flow monitoring).
All inspection and monitoring tools integrated together and tested at test bed facility (TRL6).
Further adjustments of LiDAR and FOS technology done to ensure scalability for large parts and usability in day-to-day manufacturing operations.
Economic, Green & Waste Assessment Framework
Development of the ZDM maturity model and its online assessment questionnaire.
Carrying out the first level ZDM maturity assessment as well as Eco-efficiency assessment of the industrial use-cases.
Dissemination of the developed ZDM maturity model within the ZDM cluster and at international conferences.
The main progress beyond the state of the art, during this reporting period, was made in simulation and digital tools for monitoring the infusion process:
- near real-time infusion (front flow) simulation model, actively interacting with data from sensors, was developed and experimentally tested for small
- hybrid twin model for virtual assessment of mechanical performance was developed and validated numerically at mid-size geometry
For both abovementioned models further experiments on pre-industrial validation are needed to ensure good operability and scalability.
Lastly, 6P ZDM Maturity Assessment model was applied within this period on both industry cases, proving its big value to analyse industry path towards Zero Defect.
- near real-time infusion (front flow) simulation model, actively interacting with data from sensors, was developed and experimentally tested for small
- hybrid twin model for virtual assessment of mechanical performance was developed and validated numerically at mid-size geometry
For both abovementioned models further experiments on pre-industrial validation are needed to ensure good operability and scalability.
Lastly, 6P ZDM Maturity Assessment model was applied within this period on both industry cases, proving its big value to analyse industry path towards Zero Defect.