WAVETAILOR - Modular laser sources for sustainable production of short personalized production series

The WAVETAILOR project focuses on two industrial scenarios related to complex multi-material component and assembly using laser based additive manufacturing (LBAM).

The first one is the Directed Energy Deposition (DED) of a multimaterial leading edge for a hypersonic hydrogen-driven airplane, while the second relates to the Powder Bed Fusion (PBF) of complex multi-material assembly of a drone for urban delivery.

The challenges in both cases are related to zero-defect manufacturing (ZDM), sustainability, and first-time right manufacturing. WAVETAILOR aims to solve the high-precision in complex material structure manufacturing, the disassembly, reuse, and recycling of components while reducing the environmental footprint of both the manufacturing process and the components themselves.

The team at Coventry University are responsible for work package 4 - Development of a digital twin for LBAM.

Funder: European Commission / IUK Horizon Europe Guarantee (Grant agreement ID: 101137974).
Value: €4,090,265.

WAVETAILOR is a project improving the quality and reliability of laser based additive manufacturing (LBAM); that is, 3D printing complex structures, in metal, using lasers. Today, this method for manufacturing products exhibits a lot of variability due to a complex range of factors. This leads to a trial-and-error approach with a high rate of scrap i.e. components have to be thrown away and reprinted.

However, LBAM, if optimised, can be an effective production method for low volume and/ or structures with very complex geometry. The aim of WAVETAILOR is to improve the consistency of process and quality of products made via LBAM, thus reducing scrap and waste (of raw materials and energy used in printing). This will be tackled in different ways, including new types of laser systems that are more flexible and efficient, and application of advanced digital technologies; these include machine learning and AI, and development of digital twins for monitoring and prediction.