Investigation of automatic workpiece selection for machining from bar stock inventories

John E. Leonard, Jami J. Shah

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Given a feature-based CAD model of a part's geometry, the problem is to select the shape, size and cut-off length of bar stock from which the part can be made. The standard stock shapes and sizes available in any shop vary, so the task is to select the best-suited stock geometry from the available inventory. The requirements of a system to perform this task are presented along with several alternative methods: shape coding, shrinking bounding box, silhouette projection, extremal point network, principal machining directions, and face extension. None of these methods was found to be completely satisfactory, so a hybrid method was synthesized and implemented. A coding scheme is used to select the workpiece shape, based on primary features and their relationships. Prismatic workpieces are selected by a silhouette projection method using quadtree-based matching. Pure rotational parts are distinguished from those with major axes deviations by a face extension method that looks for intersections with a candidate rotational shape. Once the overall part shape has been determined, it is matched with available workpiece shapes. The workpiece is then sized using a version of the bounding box method.

Original languageEnglish (US)
Pages (from-to)427-440
Number of pages14
JournalJournal of Intelligent Manufacturing
Volume7
Issue number6
DOIs
StatePublished - Jan 1 1996

Keywords

  • CAD
  • Computer-aided process planning
  • Group technology
  • Quadtrees
  • Solid modelling

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Investigation of automatic workpiece selection for machining from bar stock inventories'. Together they form a unique fingerprint.

Cite this