BB3.9-Simulation

Belén Hernández Gascón

  • Description

Simulation of resin injection/infusion process for the analysis and optimization of the manufacturing process of facade composite panels, including the infusion process parameters (number and position of inlets/outlets, resin permeability…).

  • Standardisation

While no specific certification is followed, the service employs procedures that align with internationally recognized standards.

  • Innovation features

The service integrates advanced resin flow simulations with ROM modeling, machine learning, and process monitoring. These cutting-edge methodologies enable precise parameter optimization and faster development of high-performance composite panels, setting it apart as an innovative manufacturing solution.

Pricing

Average cost rage: 4000-6000€/pm + Indirect Costs
Pricing: Proposal of pricing based on a "(Cost estimation) *BCR=Price" criterion. BCR parameter may be variable case by case and established based on a complexity/manpower expertise/singular hardware and software use basis. BCR= [1 Proposal of pricing based on a "(Cost estimation) *BCR=Price" criterion. BCR parameter may be variable case by case and established based on a complexity/manpower expertise/singular hardware and software use basis. BCR= [1,1-1,75],1-1,75]

Service delivery timeframe

10-30 working days (80h-240h). Depending on the complexity timeframe can be expanded.

  • Relevant Industry

RTD focused on materials development civil engineering.
Civil engineering companies.

Providers

ITA

Supporting Services

ROM modeling
Machine Learning

  • Value proposition

The service optimizes the resin injection/infusion process for manufacturing facade composite panels, reducing production costs and improving process efficiency. It provides detailed simulations that help clients refine parameters like inlets, outlets, and resin permeability, offering tailored solutions to enhance manufacturing performance.

  • Environmental and social impact

The service supports sustainability goals by using ROM modeling and machine learning to optimize resource efficiency and reduce waste in composite panel production. It contributes to durable, energy-efficient materials for sustainable infrastructure while minimizing environmental impact.

  • Geographical and/or infraestructure restrictions

Workstations and CPU-based servers.
HPC cloud computing
Commercial software licensing

  • Service Support

Kick of meeting (definition and sharing of input data for model development)
Intermediate results meeting
Final result meeting
Reporting: Report describing model development assumptions, load cases, standards followed, results (tabular, curves for variables representation, plots for results variables distributions).
MODA template.