Current feature recognition methods generally recognize and classify machining features into two classes: rotational features and prismatic features. Based on the different characteristics of geometric shapes and machining methods, rotational features and prismatic features are recognized using different methods. Typically, rotational features are recognized using two-dimensional (2-D) edge and profile patterns. Prismatic features are recognized using 3-D geometric characteristics, for example, patterns in solid models such as 3-D face adjacency relationships. However, the current existing feature recognition methods cannot be applied directly to a class of so-called mill-turn parts where interactions between rotational and prismatic features exist. This paper extends the feature recognition domain to include this class of parts with interacting rotational and prismatic features. A new approach, called the machining volume generation method, is developed. The feature volumes are generated by sweeping boundary faces along a direction determined by the type of machining operation. Different types of machining features can be recognized by generating different forms of machining volumes using various machining operations. The generated machining volumes are then classified using face adjacency relationships of the bounding faces. The algorithms are executed in four steps, classification of faces, determining machining zones, generation of rotational machining volumes and prismatic machining volumes, and classification of features. The algorithms are implemented using the 3-D boundary representation data modelled on the ACIS solid modeller. Example parts are used to demonstrate the developed feature recognition method.
All Science Journal Classification (ASJC) codes
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering