Main objectives of the project

Objective 1: Development of optimised designs based on additive manufacturing
Objective 2: Development and implementation of laser-based treatments for advanced surface functionalisation
Objective 3: Development of in-line monitoring processes
Objective 4: Development of Effective and Efficient Data Acquisition and Control Feedback Loop driven by novel Machine Learning and Artificial Intelligence
Objective 5: Processing of product demonstrators with high-performance requirements
Objective 6: Validation of lower consumption of resources, energy and gender dimensions

In the coming years, the European industry must assume the challenge of adopting clean and climate-neutral industrial value chains, producing sustainable products. Adopting digital systems will radically change the industry with products and services through innovative production processes. In particular, fully digitalised laser-based additive manufacturing methods are very versatile and thus can be implemented in different industries. Furthermore, energy saves against conventional manufacturing and material waste but also by design optimization can be achieved. However, these parts also required of additional surface treatments, which are nowadays energy and material-consuming, increasing costs and harming the environment. In addition, new concepts for increasing the added value of AM parts must be developed, for instance, by producing advanced surface functionalities in critical applications. The main objective of the CLASCO project is to develop a universal and digitalised laser-based post-process route for creating functionalised AM parts with complex shapes.
 

While the complex parts will be produced by Laser Powder Bed Fusion, Laser polishing and laser surface micro-structuring using Direct Laser Interference Patterning will be combined in a unique manufacturing system. This route will substitute several resource-consuming processes, reducing the environment's negative impact. The implementation will allow substituting standard environmental non-friendly methods and even obtaining a better performance. In addition, different in-line monitoring methods, specifically plasma sensors and infrared cameras will be implemented. In this way, a virtual representation of the process for each part will be possible (digital twin), creating an entirely digitised product. The project's impacts will be analysed to optimise the sustainability of processes and products across the entire life cycle.

Funding

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