Part and Assembly Search Based on Similarity and 3D Shape Attributes

Motivation

• Cost Estimation for Machined Parts. Nowadays, many job shops allow designers to submit a 3D model of the part to be machined over the Internet and provide a cost estimate based on the 3D part model. For some manufacturing domains such as rapid prototyping, reasonably accurate estimates of cost can be achieved by estimating volume or weight of the part. However, for some manufacturing domains such as machining, cost estimate depends on the geometric details of the object and automated procedures are not available for doing accurate cost estimation. Currently in such cases, humans perform cost estimation. In the Internet era, where designers solicit many quotes to make a decision, manual cost estimation is not economical. Cost of manufacturing a new part can be quickly estimated by finding previously manufactured parts that are similar in shape to the new part. If a sufficiently similar part can be found in the database of previously manufactured objects, then the cost of the new part can be estimated by suitably modifying the actual cost of the previously manufactured similar part.
• Part Family Formation. In many manufacturing domains such as sheet metal bending, machine tools can be setup to produce more than one type of part without requiring a setup or tool change. However, parts need to be shape compatible in order for them to share common tools and setups. Therefore, in order to find common tools and setups, geometrically similar and therefore compatible parts need to be grouped into families. Shared tools and setups can be used to manufacture objects in the same family and therefore result in significant cost savings.
• Reduction in Part Proliferation By Reusing Previously Designed Parts. Reusing design/manufacturing information stored would result in a faster and more efficient design process. While designing a new part the designer can refer to existing designs and utilize the components used previously. Let us consider the design of the shaft of a turbine engine. Usually the designer has two options. The first option is to design the shaft from scratch and go through the process and manufacturing planning. The second option is to refer to the database of existing designs, and select an existing shaft and either use it as it is or make minor modifications to it (e.g., drill a few holes or cut a few slots).

Technical Approach

• Feature-Based Techniques:This method uses feature information obtained from feature-based modeling software such as Pro/E or SolidWorks to assess similarity between parts. We can use either design features or manufacturing features. We utilize feature vectors consisting of feature position vectors, feature orientation vectors, feature types, and feature parameters as a basis to assess shape similarity. We have defined a distance function between two sets of feature vectors. The distance between the feature vectors is used as a measure of similarity between the two parts. The features vectors provide a very convenient way of including critical details and filtering out irrelevant details in search for similar parts.
• Gross-Shape Based Techniques: The gross-shape based technique uses several signatures to identify existing parts similar to the query part. The signatures are applied sequentially to improve the efficiency and accuracy of the comparison. The following types of signatures are used to compare the query part with database part to assess similarity: part volume and surface area, basic shape statistics such as the types of surfaces and their corresponding areas, gross shape complexity, and detailed shape complexity that includes the surface area and curvature information

• Customizability: Our method allows the user to customize the search criteria by letting the user select the important feature characteristics that s/he wants to consider such as feature type, feature volume etc. Also the distance function used for comparison can also be customized so that some feature characteristics are given more importance than others.
• Manufacturing Information: Manufacturing information such as tolerance, surface finish etc. that is associated with a feature can also be used. Thus two parts having the same shape but largely different tolerance requirements will not be considered as similar.
• Applicable to Assemblies: Our method utilizes the feature information obtained from a feature tree. It can be easily extended to use assembly feature information obtained from an assembly tree.

Related Publications

• A. Cardone, S.K. Gupta, and M. Karnik. A survey of shape similarity assessment algorithms for product design and manufacturing applications. Journal of Computing and Information Science in Engineering, 3(2):109--118, 2003.
• M. Karnik, S. K. Gupta, and E. B. Magrab. Geometric algorithms for containment analysis of rotational parts. Computer Aided Design, 37(2):213--230, February 2005.
• A. Cardone, S.K. Gupta, and M. Karnik. Identifying similar parts for cost estimation. In ASME Design for Manufacturing Conference, Salt Lake City Utah, September 2004.
• M. Karnik, D. K. Anand, E. Eick, S. K. Gupta, and R. Kavetsky. Integrated visual and geometric search tools for locating desired parts in a part database. CAD Conference, Bangkok, Thailand, 2005.
• A. Deshmukh, S.K. Gupta, M. V. Karnik, and R. Sriram. A system for performing content-based searches on a database of mechanical assemblies. ASME International Mechanical Engineering Congress & Exposition, Orlando, FL, November 2005.
• Cardone and S.K. Gupta. Shape Similarity Assessment Based on Face Alignment using Attributed Applied Vectors. CAD Conference, Phuket Island, Thailand, June 2006.
• S.K. Gupta, A. Cardone, and A. Deshmukh. Content-Based Search Techniques for Searching CAD Databases. CAD Conference, Phuket Island, Thailand, June 2006.
• A. Cardone; S.K. Gupta, A. Deshmukh, and M. Karnik. Machining feature-based similarity assessment algorithms for prismatic machined parts. Computer Aided Design, 8(9):954--972, 2006.

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