CARTIF Projects
DIAMETER
Demonstration of a sustainable circular-by-design manufacturing system based on additive manufacturing
Description
The DIAMETER project will contrast the physical-experimental results of 3D metal additive manufacturing processes with computational simulations, with the aim of predicting the behaviour of the parts under different process modifications. The analysis of mechanical responses, such as stresses and deformations, will provide in-depth knowledge of both the part and the process, identifying possible failures, reducing waste, improving quality and assessing the need to integrate post-processes, such as hybrid manufacturing combining additive and subtractive techniques.
From a combination of scenarios and results, reliable synthetic data will be generated, which will be transformed into quantifiable metrics under a sustainability approach. This data will feed an artificial intelligence-based system designed to optimise automated decision making in metal additive manufacturing configuration and procedures, thus facilitating a more efficient design from the early stages of development.
Objectives
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- Predicting the behaviour of parts under different manufacturing conditions without the need to physically carry out each of the processes.
- Establish a hybrid manufacturing system that combines additive manufacturing and digital tools to optimise processes.
- Evaluate life cycle analyses (LCA) of products manufactured with different manufacturing systems, to identify and contrast best practices that optimise sustainability and favour the adoption of circular manufacturing models.
- Development of an AI-assisted algorithm to calculate and evaluate the ecological and economic impacts of various methods.
- Create the necessary solutions and strategies to facilitate the efficient and sustainable transition of the 3D metal manufacturing sector towards a circular economy.
Actions
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- Develop a vision system for dimensional measurement and surface verification during the process, adapted to metal 3D printing work environments.
- Identify by means of numerical simulation critical areas of the parts under consideration and optimise their manufacturing position and the strategy of the manufacturing supports accordingly.
- Develop machine learning algorithms to predict environmental impacts based on a series of synthetic data extracted from simulations and detailed process information.
Expected Results
- Improving the quality and precision of parts.
- Optimisation of manufacturing.
- Improved sustainability.
R&D Line
- Development of AI-based solutions for decision support in construction
Partners
Horizon Europe
101177422
Total Budget: 5,999,845€
CARTIF Budget: 324,625€
CARTIF Funding: 324,625€
Duration: 01/11/2024 – 01/11/2028
Responsible
Norberto Ibán
Networking
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