Optimizing material and process parameters in laser engineered net shaping using liquid neural networks

> 0.9 for key quality measures on the test set) and effective multi-objective optimization. The optimized parameters yield improved microhardness (+ 12.5%), reduced dilution (18%), and improved cladding consistency (CUI = 0.97). Results demonstrate that this approach can achieve defect-minimized, energy-efficient additive manufacturing. We lay a foundation for closed loop control and digital twin integration for advanced laser cladding applications.