<p>Gamma-ray column scanning is a non-destructive testing technique used to inspect the internal conditions of distillation columns by detecting blockages, malfunctions, or structural anomalies. While conventional scanning provides one-dimensional profiles, gamma-ray laminography enhances this approach by acquiring multiple angular projections to reconstruct detailed two-dimensional cross-sectional images. This study employs the Particle and Heavy Ion Transport code System (PHITS) to simulate gamma-ray laminography of a distillation column. The column's geometry and material composition are modeled within PHITS, and gamma-ray sources and detectors are configured to move vertically along the column to simulate multi-angle projections. The resulting gamma-ray transmission data is exported and processed using a Python-based image reconstruction framework. Algorithms such as simple back projection and Simultaneous Algebraic Reconstruction Technique (SART) are applied to generate vertical 2D images of the column’s internal structure. The reconstructed images demonstrate the feasibility and effectiveness of combining PHITS simulations with computational reconstruction techniques for advanced non-destructive evaluation of distillation columns.</p>