Optimizing Tensile Strength of Low-Carbon Steel Shafts with Stacked Ring Substrates in WAAM Using Taguchi and Random Forest Regression

Wire Arc Additive Manufacturing (WAAM) enables cost-effective fabrication of complex metallic components but faces challenges in achieving consistent tensile strength for cylindrical parts with intricate internal features (e.g., cooling channels, helical grooves), where conventional machining is often infeasible or prohibitively expensive. This study introduces a novel stacked ring substrate strategy with pre-formed low-carbon steel rings defining complex internal geometries, followed by external WAAM deposition using ER70S-6 wire to overcome these limitations. Five process parameters (welding current: 110-130 A; offset distance: 2.5-3.0 mm; Step Length: rotary to straight; torch speed: 400-500 mm/min; weld thickness: 2.0-3.0 mm) were optimized using a Taguchi L25 orthogonal array (25 runs in triplicate). ANOVA identified Step Length as the dominant factor, with straight paths significantly reducing thermal cycling and improving interlayer bonding, alongside a notable current × speed interaction. Optimal settings achieved tensile strengths of 280-290 MPa, significantly below wrought ER70S-6 benchmarks (400-550 MPa) due to interfacial weaknesses at ring fusion zones and thermal accumulation from stacked cylindrical geometry, a limitation acknowledged in the absence of microstructural or thermal history data. A Random Forest Regressor predicted strength with R² = 0.9312, outperforming conventional models. This hybrid approach significantly enhances design freedom and mechanical reliability for high-value cylindrical components in aerospace and tooling, establishing a scalable, data-driven framework for geometry-constrained WAAM optimization.