SCAN to CAD Process

The scan-to-CAD process starts with capturing a high-quality 3D scan of the physical product, resulting in a raw mesh file (typically STL or OBJ) that represents the object's surface geometry with millions of points and triangles.

From there, the workflow refines this raw data through specialized stages to arrive at precise, editable CAD geometry suitable for further design, manufacturing, or analysis.

First, the mesh undergoes targeted refinement and repair in a dedicated mesh-editing environment. This stage focuses on correcting common scan imperfections—such as holes, noise, non-manifold edges, or irregularities—while preserving critical details and optimizing the overall structure for downstream use.

Next, the cleaned mesh is brought into Rhino, where it serves as the foundation for advanced modeling. Here, the geometry transitions into a subdivision surface form, allowing smooth, organic reshaping and control over curvature with greater flexibility than a raw mesh.

Once the SubD representation achieves the desired shape and quality, it converts into NURBS surfaces. This step produces mathematically precise, parametric surfaces that maintain high fidelity to the original scan while enabling exact tolerances and compatibility with traditional CAD tools.

Finally, the NURBS surfaces are used to generate true solid body geometry—closed, watertight volumes that support operations like boolean functions, shelling, filleting, or export to manufacturing formats (e.g., STEP or IGES). This solid model becomes fully parametric and ready for constraint-based design, reverse engineering modifications, or integration as a reference in new product development.

This sequence delivers exceptional accuracy (often sub-0.1mm deviation when handled carefully), dramatically reduces design iterations by providing a faithful digital twin of the physical part as a built-in constraint, and bridges the gap between imperfect scan data and professional-grade CAD solids—without relying on manual tracing or approximations. It's particularly powerful for complex or organic shapes where precision fit and manufacturability matter most.