Prediction of Neutral Layer Shifting in Thin Sheet Metal Bending: A Combined Finite Element Simulation, Machine Learning, and Experimental Study

To address poor dimensional precision and compromised service performance caused by neutral layer displacement in sheet metal bending, this study integrates numerical simulation and experimental validation to establish a bending process database for thin sheets of various thicknesses. Key factors affecting neutral layer displacement are analyzed, and a prediction model for the neutral layer coefficient k is developed, with an absolute validation error below 0.05 in k for the reported verification cases. A differentiated parameter optimization strategy is proposed: thinner sheets use smaller bending radii and higher speeds; as thickness increases, the radius is enlarged and speed reduced. For sheets thicker than 1.0mm, a larger radius and strictly controlled speed are required to inhibit abnormal displacement. The findings provide a theoretical basis for precise parameter optimization and significantly improve sheet metal forming quality.