HYBRID MANUFACTURING FOR SPACE APPLICATION - EXPRO PLUS

To advance hybrid manufacturing strategies that integrate conventional and advanced techniques to enhance the performance, functionality and competitiveness of space hardware.Description:Hybrid manufacturing combines subtractive methods (e.g. milling, turning,grinding) with additive processes(e.g. powder bed processes, direct energy deposition). It may also include fabrication/joining steps like welding,bonding or brazing. This approach aims to overcome limitations of individual processes, enabling theproduction ofhigh-performance, competitive components. Such methodologies are of growing relevance particularly in propulsion, thermal management and structural systems. The key drivers include:- Geometric complexity: enabling the manufacture of intricate, topology-optimisedstructures difficult to realiseby conventional means alone.- Material efficiency: by adding material only where needed, hybrid manufacturing reduces waste and optimizes material usage.- Functional performance: enabling graded material properties, local reinforcements or tailored functionality.- Cost and lead time: consolidating steps, minimising waste and enabling complex geometries, though it mayrequire specialised planning, equipment and qualification.- Design flexibility: greater customization and flexibility in design, making it ideal for producing bespoke or low volume parts.This activity encompasses the following tasks:- Survey of relevant techniques, materials and equipment capabilities relevant to a hybrid manufacturing approach.- Selection of two representative case studies with associated requirements (e.g. one propulsion component, one thermal management part).- Design and definition of the hybrid manufacturing route for each case study.- Manufacturing and functional testing of demonstrators. The utilisation of new digital methods for supportinghybrid manufacturing decisions is welcomed. This may include artificial intelligence techniques, such asdeep/federated learning techniques, as well as a focus on use-cases of generatively designed parts (whichinherently benefit from the hybrid manufacturing techniques), alongside the artificial intelligence and machine learning data-driven learning.- Economic analysis, including cost comparison with conventional approaches and life-cycle considerations.Deliverables: Breadboard, ReportNOTE: This activity is currently in the GSTP Work Plan but will only be implemented after confirmation of financial support from Delegations. The final list of participating states will be known at tender issue.