The WAVETAILOR project pioneers sustainable Laser-Based Additive Manufacturing (LBAM) by employing robust Digital Twin technology. This innovation ensures first-time perfect assemblies and achieves an 80% reduction in scrap. Z Prime’s platform integrates bespoke Intelligent Data Acquisition, analytics, machine learning, and AI solutions to optimise the manufacture of high-precision aerospace products with complex geometries.
Challenges
The LBAM industry must address high scrap rates, energy inefficiency, and the need for frequent trial-and-error adjustments resulting from not fit-for-purpose processes. The only way to address increasing costs and negative environmental impacts is to streamline production, reduce waste, and improve overall efficiency. This requires a new, AI-driven approach.
The Project
To ensure first-time perfect assemblies, WAVETAILOR uses a robust Digital Twin to simulate and optimise the entire manufacturing process, providing a virtual replica for real-time adjustments and improvements. The project integrates multi-scale models with machine learning algorithms to optimise component designs and accurately predict outcomes, reducing trial-and-error and enhancing precision.
By combining data from various sensors to enhance AI/ML algorithms through sensor signal fusion, WAVETAILOR enables precise process parameter optimisation. Emphasising sustainability, the project reduces scrap by 80%, improves energy efficiency, and minimises the environmental footprint of the manufacturing process.
Z Prime’s Contributions
Z Prime developed bespoke Machine Learning, Monitoring, and Control Algorithms to optimise high-precision manufacturing through Laser Additive Manufacturing. The platform supports the production of aerospace products with complex geometries, enabling high customisation across various markets. Z Prime’s solutions significantly reduce waste, defects, energy consumption, and GHG emissions.
Benefits
- Reduced Scrap: Achieves an 80% reduction in scrap, significantly lowering material waste and associated costs.
- Enhanced Precision: Ensures first-time perfect assemblies through advanced simulation and optimisation techniques.
- Improved Efficiency: Optimises process parameters in real-time, enhancing the overall efficiency of the manufacturing process.
- Economic Gains: Elevates the economy of LBAM by reducing waste, improving energy efficiency, and lowering operational costs.
- Sustainability: Supports sustainable manufacturing practices, reducing environmental impact and promoting energy-efficient processes.
Conclusion
The WAVETAILOR project represents a significant advancement in Laser-Based Additive Manufacturing (LBAM). By integrating robust Digital Twin technology, multi-scale models, machine learning, and sensor signal fusion, WAVETAILOR optimises component designs and process parameters to ensure first-time perfect assemblies and substantial scrap reduction. This innovative approach not only addresses the critical challenges of the LBAM industry but also promotes sustainability and economic efficiency. The successful implementation of WAVETAILOR demonstrates its potential to transform additive manufacturing, setting new standards for quality, efficiency, and environmental responsibility.
