2000 (and backfills for previous years) / DB reference years
PREV and NEXT link to numerically adjacent references for this DATABASE UPDATE.
CONTENTS links to the title list for this UPDATE's references.
Author Jha, Kailash. Gurumoorthy, B. Institution Indian Inst of Science, Bangalore, India
Source Computers in Industry. v 42 n 1 2000. p 13-32.
Abstract In this paper, we focus on the problem of extracting multiple feature models of a part. Most of the efforts reported to date extract multiple feature models that contain only machining (negative) features. While this is useful for the task of process planning, it is desirable to have multiple interpretations of a part that are useful in other domains as well. We define three types of multiple feature interpretations or models, (1) only positive, (2) mixed and (3) only negative. Identifying feature models with only positive features is useful in reasoning about fabrication processes like welding, layered manufacturing processes and in design analysis. Feature sets consisting of both positive and negative features are useful in efficient modelling of geometry. Feature models with only negative features are useful in process planning for machining. We present an algorithm that generates multiple feature interpretations within and across domains. The algorithm generates multiple feature interpretati ons for parts, which have a through feature in any one domain. Parts with interacting and intersecting features ending on single face are handled. Results of implementation on typical solids are reported. (Auth abstract) [References: 24] XX