The primary goal of this project is to develop a search system for engineering parts. It is expected that this system can be used in conjunction with PLM systems or can be customized as a standalone feature in CAD repositories. A significant amount of knowledge generated during design and manufacturing is associated with the 3D model. However, text-based searching is not robust primarily for the following reasons: (a) All models will not have a well-defined attached context. (b) Keywords such as project names or part names may be unknown to the user. (c) Context may be too narrow or too broad to retrieve relevant models. (d) Context changes with time, such as when designers or naming conventions change. Thus, a search system which is capable of retrieving similar 3D models based on their shape will also retrieve related knowledge.

Designers spend a significant amount of time searching for information that is availablebut cannot be located through traditional methods. Rectification of errors that have been committed due to lack of information is a costly way to learn. Nevertheless this has become a de facto process for new product design. A significant amount of information generated during the lifecycle of a product is associated with 3D models. Reuse of this information can significantly shorten lead times and reduce costs during a product's lifecycle. This project deals with an innovative approach to search for 3D models. 3D search offers an alternative means to retrieve design knowledge that is intimately associated with 3D geometry. 3D models are represented by a hierarchical skeletal graph representation rich with local information. The skeletal graph representation preserves geometry and topology of the model with good fidelity. Critical issues such as algorithms for converting a model into a skeletal graph, search system efficiency, semantic gap reduction and the subjectivity of the similarity definition are addressed.


  • Mechanical Engineering:
    Dr. Karthik Ramani, Natraj Iyer, Kuiyang Lou, Subramaniam Jayanti, Yagnanarayanan Kalyanaraman, Suyu Hou, Min Liu, Noel Titus
  • Computer Science:
    Dr. Sunil Prabhakar
  • Psychological Sciences:
    Dr. Zygmunt Pizlo

Indiana 21st Century Research and Technology Fund
Purdue University Faculty Scholar Award



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