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Journal ArticleDOI

Spatial reasoning for the automatic recognition of machinable features in solid models

TLDR
In this article, an automatic feature recognizer decomposes the total volume to be machined into volumetric features that satisfy stringent conditions for manufacturability, and correspond to operations typically performed in 3-axis machining centers.
Abstract
Discusses an automatic feature recognizer that decomposes the total volume to be machined into volumetric features that satisfy stringent conditions for manufacturability, and correspond to operations typically performed in 3-axis machining centers. Unlike most of the previous research, the approach is based on general techniques for dealing with features with intersecting volumes. Feature interactions are represented explicitly in the recognizer's output, to facilitate spatial reasoning in subsequent planning stages. A generate-and-test strategy is used. OPS-5 production rules generate hints or clues for the existence of features, and post them on a blackboard. The clues are assessed, and those judged promising are processed to ensure that they correspond to actual features, and to gather information for process planning. Computational geometry techniques are used to produce the largest volumetric feature compatible with the available data. The feature's accessibility, and its interactions with others are analyzed. The validity tests ensure that the proposed features are accessible, do not intrude into the desired part, and satisfy other machinability conditions. The process continues until it produces a complete decomposition of the volume to be machined into fully-specified features. >

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Citations
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Proceedings ArticleDOI

Topology matching for fully automatic similarity estimation of 3D shapes

TL;DR: A novel technique is proposed, called Topology Matching, in which similarity between polyhedral models is quickly, accurately, and automatically calculated by comparing Multiresolutional Reeb Graphs (MRGs), which operates well as a search key for 3D shape data sets.
Journal ArticleDOI

Manufacturing feature recognition from solid models: a status report

TL;DR: The paper gives an overview of the state-of-the-art in feature recognition research by focusing on the three of the major algorithmic approaches for feature recognition: graph-based algorithms, volumetric decomposition techniques, and hint-based geometric reasoning.
Journal ArticleDOI

Survey paper: A review of automated feature recognition with rule-based pattern recognition

TL;DR: A novel, detailed classification of developed AFR systems has been introduced and potentials and limitations of these approaches are discussed, and directions for further research work are emphasized.
Journal ArticleDOI

Feature-based reverse engineering of mechanical parts

TL;DR: A prototype of a reverse engineering system which uses manufacturing features as geometric primitives is described, which has two advantages over current practice: the resulting models can be directly imported into feature-based CAD systems without loss of the semantics and topological information inherent in feature- based representations.
Journal ArticleDOI

Automatic recognition of interacting machining features based on minimal condition subgraph

TL;DR: The conventional, graph-based recognition method is combined with hint-based feature recognition to recognize and extract alternative interpretations of interacting features, and a new classification of feature interactions is presented.
References
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Journal ArticleDOI

Representations for Rigid Solids: Theory, Methods, and Systems

TL;DR: A coherent view, based on sound theoretical principles, of what is presently known about the representation of solids is provided by providing a simple mathematical framework for characterizing certain important aspects of representations, for example, their semantic (geometric) integrity.
Journal ArticleDOI

A blackboard architecture for control

TL;DR: The paper shows how opm, a blackboard control system for multiple-task planning, exploits these capabilities and shows how the architecture would replicate the control behavior of hearsay-ii and hasp.
Journal ArticleDOI

The blackboard model of problem solving

Penny Nii
- 01 Jul 1986 - 
TL;DR: The first blackboard system was the HEARSAY-II speech understanding system (Erman et al.,1980) that evolved between 1971 and 1976 as mentioned in this paper, and many systems have been built that have similar system organization and run-time behavior.
Book

Programming expert systems in OPS5: an introduction to rule-based programming

TL;DR: What do you do to start reading programming expert systems in ops5 an introduction to rule based programming the addison wesley series in artificial intelligence?
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