Using shape distributions to compare solid models
Proceedings of the seventh ACM symposium on Solid modeling and applications
Scale-space representation of 3D models and topological matching
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
3D zernike descriptors for content based shape retrieval
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Automated learning of model classifications
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Content-based Three-dimensional Engineering Shape Search
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Enhancing Stochastic Search Performance by Value-Biased Randomization of Heuristics
Journal of Heuristics
Content-based assembly search: A step towards assembly reuse
Computer-Aided Design
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
Three-dimensional shape searching: state-of-the-art review and future trends
Computer-Aided Design
Shape-based searching for product lifecycle applications
Computer-Aided Design
Extracting common design patterns from a set of solid models
Computer-Aided Design
Shape-based search of mechanical CAD models for product data management
International Journal of Computer Applications in Technology
Technical Section: Automatic discovery of common design structures in CAD models
Computers and Graphics
Design reuse oriented partial retrieval of CAD models
Computer-Aided Design
Active multiple kernel learning for interactive 3D object retrieval systems
ACM Transactions on Interactive Intelligent Systems (TiiS)
Automatic comparison and remeshing applied to CAD model modification
Computer-Aided Design
Retrieval of high-dimensional visual data: current state, trends and challenges ahead
Multimedia Tools and Applications
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Solid Models are the critical data elements in modern Computer-Aided Design (CAD) environments, describing the shape and form of manufactured artifacts. Their growing ubiquity has created new problems in how to effectively manage the many models that are now stored in the digital libraries for large design and manufacturing enterprises. Existing techniques from engineering literature and industrial practice, such as group technology, rely on human-supervised encodings and classification; techniques from the multimedia database and computer graphics/vision communities often ignore the manufacturing attributes most significant in the classification of models. This paper presents our approach to manufacturing similarly assessment of solid models of mechanical parts based on machining features. Our technical approach is three-fold: (1) perform machining feature extraction to map the solid model to a set of STEP AP 224 machining features; (2) construct a model dependency graph from the set of machining features; (3) find the nearest neighbors to the query graph using an iterative improvement search across a database of other models. We also present empirical experiments to validate our approach using our testbed, the National Design Repository (http://www.designrepository.org).The contribution of this research is the first fully automated technique for machining feature-based comparisons of mechanical artifacts. We believe that this work can lead to radical changes in the way in which design data is managed in modern engineering enterprises.