A new methodology for extracting manufacturing features from CAD system

Abstract

In recent years, various researchers have come up with different ways and means to integrate CAD and CAM. Automatic feature recognition from CAD solid systems highly impacts the level of integration. CAD files contain detailed geometric information of a part, which are not suitable for using in the downstream applications such as process planning. Different CAD or geometric modeling packages store the information related to the design in their own databases. Structures of these databases are different from each other. As a result no common or standard structure has been developed so far, that can be used by all CAD packages. For that reason this paper proposes an intelligent feature recognition methodology (IFRM) to develop a feature recognition system which has the ability to communicate with various CAD/CAM systems. The proposed methodology is developed for 3D prismatic parts that are created by using solid modeling package by using CSG technique as a drawing tool. The system takes a neutral file in Initial Graphics Exchange Specification (IGES) format as input and translates the information in the file to manufacturing information. The boundary (B-rep) geometrical information of the part design is then analyzed by a feature recognition program that is created specifically to extract the features from the geometrical information based on a geometric reasoning approach by using object oriented design software which is included in C++ language. A feature recognition algorithm is used to recognize different features of the part such as step, holes, etc. Finally, a sample application description for a workpiece is presented for demonstration purposes.

Introduction

The main objective of any manufacturing organization is to produce high quality products at the lowest possible cost. The growing complexity of achieving this objective, with sharply rising costs and increased competition, has forced the industry to look for alternatives to the traditional approaches to design, manufacturing and management. Many industries are adopting a concurrent engineering (CE) approach to develop and produce new products in the most efficient manner (Reiter, 2003, Rouibah and Casekey, 2003). Computer Aided Process Planning (CAPP) systems can help to reduce planning time and increase consistency and efficiency (Nagaraj & Gurumoorthy, 2002). However, the main problem of transferring CAD (Computer Aided Design) data to a downstream CAM (Computer Aided Manufacturing) system, in order to develop Computer Integrated Manufacturing (CIM) environment, is the lack of neutral formats as well as content to convey the CAD information (Ahmad and Haque, 2001, Natekar et al., 2004).

The integration of Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) has received significant attention in the recent years according to the development of faster computing power tools. However, the actual integration between CAD and CAM, for the downstream applications such as process planning, can be achieved only when the manufacturing information can be obtained directly from 3D solid model and hence automate the process planning functions (Chang et al., 2002, Mansour, 2002, Miao et al., 2002). This automatic extraction of manufacturing information from CAD systems play an important role to facilitate the concurrent engineering concept in order to achieve the link between the design and manufacturing activities. This successful link can be considered as fundamental step to automate the product development from the design stage all the way to manufacturing and shipping stages. Hence, the total life cycle of the product can be reduces dramatically (Bhandarkar et al., 2000, Marri and Kobu, 2003, Meeran et al., 2003, Stage et al., 1999).

One of the foundation tasks in a Computer Integrated Manufacturing (CIM) environment is to extract and identify the information in the CAD model file (Groover, 2001, Han and Han, 1999, Roucoules et al., 2003). The conventional approach to feature extraction is accomplished by the human planner examining the part and recognizing the features designed into the part. Automated feature recognition can best be facilitated by CAD systems capable of generating the product geometry based on features, thereby making it possible to capture information about tolerance, surface finish, etc. (Fu, Lu, Ong, Lee, & Nee, 2003). However, such CAD systems are not yet mature and their wide usage in different application domains remains to be seen. It is therefore necessary to consider developing an intelligent feature recognition system to extract features from part geometry. In this paper, a methodology for feature analysis and extraction of prismatic parts for CAM applications is developed and presented. This approach aims to achieve the integration between CAD and CAM.

CAD files contain detailed geometric information of a part, which are not suitable for using in the downstream applications such as process planning. Different CAD or geometric modeling packages store the information related to the design in their own databases (Tseng & Joshi, 1998). Structures of these databases are different from each other. As a result no common or standard structure has been developed so far, that can be used by all CAD packages. For that reason, this paper will propose an intelligent feature recognition methodology (IFRM) to develop a feature recognition system which has the ability to communicate with various CAD/CAM systems. The proposed methodology is developed for 3D prismatic parts that are created by using solid modeling package by using constructive Solid Geometry (CSG) technique as a drawing tool. The system takes a neutral file in Initial Graphics Exchange Specification (IGES) format as input and translates the information in the file into manufacturing information. The boundary (B-rep) geometrical information of the part design is analyzed by a feature recognition program that is created specifically to extract the features from the geometrical information based on a geometric reasoning approach by using object oriented design software which is included in C++ language.

Including this introductory section, the paper is organized into five sections. Section 2 describes literature review of the previous research efforts in the area of feature extraction and recognition. The proposed approach for feature extraction is presented in Section 3. The implementation of the suggested approach is demonstrated through an example in Section 4. Finally, Section 5 presents conclusions.