Name
Abstract | ||
|---|---|---|
Solving the machine feature recognition problem has been widely recognized as a cornerstone for developing an automated process planning system directly linked to a CAD system. Various recognition techniques have been developed; however, they are in general deficient in robustness. That is, valid machined features may not be recognized and features which are recognized may not be valid in practice. This paper is intended to analyse the existing machined feature recognition techniques, which are based on the B-rep solid modelling scheme, in order to give the reasons why the robustness problem would occur. The pros and cons for recognizing machined features are also analysed. Finally, a cutter selection methodology, known as process requirement modelling, is introduced; this methodology seems to provide a promising way to solve the machined feature recognition problem. Copyright (C) 1996 Elsevier Science Ltd. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1016/0010-4485(95)00075-5 | COMPUTER-AIDED DESIGN |
Keywords | Field | DocType |
machined feature recognition, cutter selection, computer-aided process planning | Computer-aided process planning,Mathematical optimization,Computer Aided Design,Feature recognition,Solid modelling,Robustness (computer science),Artificial intelligence,Engineering,Cad system,Machine learning | Journal |
Volume | Issue | ISSN |
28 | 8 | 0010-4485 |
Citations | PageRank | References |
17 | 1.10 | 9 |
Authors | ||
2 | ||