Abstract
A 3D solid model is used in various processes such as design, engineering evaluation, drafting, manufacturing, and so on. Most commercial CAD tools support functions to generate engineering drawings from solid models automatically. However, It is a time-consuming and skill-required job to create a complicated 3D solid model. Parametric modeling is an approach to construct and to modify model geometry with geometric constraints. Nowadays, freeform surfaces are frequently used in a product design in order to meet customers’ aesthetic needs. Freeform modeling requires considerably more time and effort than ordinary mechanical modeling. It is difficult to impose parametric constraints on freeform models since the shape of freeform models is fully arbitrary as its name implies. As a result, parametric modeling has not been popular in freeform modeling. The primary objective of this research is to simplify the geometric processing required by freeform product customization. We develop a statistical model and a reliable Semantic Parametric Design algorithm applicable to various areas including human body shape, and garment design. The algorithm helps user construct a new model which is conformed to its semantic parameter and the user’s request. We build a reliable object database and compute models and semantic parameters as a statistical linear system. After linking each parameters and triangular mesh of corresponding models, we can generate a new model fitted with the user’s needs by this association. Besides, we provide a method to inspect if the new modified value is reasonable. This makes great helpful for design efficiency.