Single Point Incremental Forming (SPIF) has attracted increasing attention as a flexible manufacturing route for complex sheet metal components; however, its broader industrial adoption remains constrained by limited predictive accuracy in thickness distribution and surface integrity, particularly for non-axisymmetric geometries. In this study, a combined numerical-experimental framework is developed to investigate and validate the SPIF process applied to truncated quadrilateral panels fabricated from AA1050 aluminum alloy. A three-dimensional finite element model incorporating a Voce strain hardening law, calibrated from uniaxial tensile experiments, is employed to accurately capture material anisotropy and plastic deformation behavior. The numerical predictions of wall thickness distribution and thinning evolution are systematically compared with experimental measurements along the inclined walls of the formed components. The results demonstrate a high level of agreement, with an average thickness deviation below 2%, confirming the reliability of the proposed material model and simulation strategy for complex, non-axisymmetric SPIF geometries. Beyond thickness prediction, the study provides a detailed experimental assessment of surface roughness evolution as a function of key process parameters. The effects of tool diameter (6–14Formula: see textmm) and vertical downstep (0.5–1.5Formula: see textmm) on surface integrity are quantified under controlled forming conditions. The findings reveal that increasing tool diameter effectively reduces surface waviness by enlarging the tool-sheet contact area, while decreasing the downstep significantly enhances surface smoothness by promoting closer conformity between successive tool paths. Comparative analysis indicates that downstep exerts a more dominant influence on surface quality than tool diameter. The originality of this work lies in the integrated validation of thickness uniformity and surface integrity for truncated quadrilateral SPIF components using a calibrated Voce-based constitutive framework, combined with a systematic evaluation of surface roughness control mechanisms. The results provide practical guidelines for parameter optimization and offer clear implications for high-precision manufacturing applications, including aerospace panels, biomedical components, and customized engineering structures.
Nguyen et al. (Sat,) studied this question.