Generative regular‐freeform surface recognition for generating material removal volume from stock model

The present paper illustrates the development of generative surface recognition for regular and freeform. To obtain the final form of product, material removal volume generation from a stock model is also discussed. Only a few studies integrated the regular and freeform surfaces to provide a comprehensive definition of surface recognition as well as for the volumetric estimation of removal material in finishing and roughing operations. The current research deploys a comprehensive surface recognition approach that can recognise both regular and freeform surfaces based on the geometry as well as loop entity of a face. In contrast to the regular surface that can be categorised into a particular group of geometrical shape, such as cylindrical shape, the proposed approach enables the recognition of a freeform surface that cannot be defined as a generic geometrical shape. In addition, the new method also simplifies the existing surface recognition for regular surfaces. The material removal volumes created consist of machining volumes for finishing and roughing operations needed to be machined to obtain the final form of the product. The present research provides a unique user customisation feature that enables user to specify the volumetric thickness for material removal volume in the finishing operation as well as the size for the stock model. These estimated volumes are prepared for subsequent manufacturing applications, such as sequencing of machining operation.