A review of machining feature recognition methodologies

Abstract

In a continuing quest to decrease the time interval between conceptualisation of a product and its first production, the use of information technology in design, analysis and manufacturing practice has been actively researched. The design engineer designs a part and sends the final design to the manufacturing engineer, who re-interprets the design and plans the manufacturing activities to produce the part. These two sections generally work in isolation from each other, resulting in high lead-time, duplication of data, inconsistent product data and sometimes redesign of a product. Feature recognition is a process of reinterpreting a design model database for automating downstream manufacturing activities. Active research in this field has developed numerous techniques such as syntactic pattern recognition, graph theory, volume decomposition, artificial intelligence and hint-based, and neural network-based systems. This paper presents a critical review of strengths and weaknesses of these approaches.

Keywords:

• feature recognition
• graph-based
• hint-based
• volume decomposition
• neural network-based
• CAPP