Recognition of features in sheet metal parts manufactured using progressive dies

Yang Yang, Srichand Hinduja*, Oladele Owodunni, Robert Heinemann

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Feature recognition is an important stage in digital manufacturing as it supports activities such as automated process planning and part re-design. This paper describes a two-stage algorithm for recognising features in sheet metal parts which are manufactured using progressive dies. Representation of the part in neutral format (STEP AP203) facilitates the first stage of this algorithm in which the thickness faces are extracted in the form of chains. In the second stage, an extracted chain of faces is classified by, first, determining its topological and geometric characteristics and then comparing its characteristics with pre-set attributes for each feature. The system was developed in C++ and has been successfully tested on representative parts containing features ranging from simple bends to composite features, such as a cut-out with lance.
Original languageEnglish
JournalComputer-Aided Design
Volume134
Publication statusPublished - May 2021

Fingerprint

Dive into the research topics of 'Recognition of features in sheet metal parts manufactured using progressive dies'. Together they form a unique fingerprint.

Cite this