Wall thickness is one of the most directly actionable measurements in volumetric CT analysis. Whether assessing compliance with geometric tolerances, identifying thin-wall failure risks in a casting, or validating a printed polymer part against a nominal CAD model, the underlying measurement task is the same: determine the shortest material distance from every point on the outer surface to the opposing inner boundary. This post demonstrates how to automate the complete pipeline in Volvicon — from raw volume data through to a statistical report — using the Python Scripting API.

Industrial CT inspection workflows typically involve three sequential stages: volume reconstruction from raw projections, defect characterisation within the reconstructed volume, and export of quantitative results for reporting or downstream processing. Each stage carries its own set of parameters and potential failure modes. This post walks through how to automate all three stages in Volvicon using the Python Scripting API, drawing on a worked example with cone beam CT data.