Part and Assembly Search Based on Similarity and 3D Shape Attributes
Main Participants: Satyandra K. Gupta, Antonio Cardone, Mukul Karnik, and Abhijit Deshmukh
Sponsors: This project is being sponsored by the Naval Surface Warfare Center at Indian Head, Maryland and the Center for Energetic Concepts Development at the University of Maryland.
Keywords: Shape Similarity, Shape Search, Part Retrieval, and Assembly Retrieval
Motivation
Intuitively, if two products are similar, it is possible to reuse information about one product to derive corresponding information about the other one. There are many possible applications where reuse of information can be of significant value. Representative examples include part-family formation, redesign suggestion generation, supplier selection, cost estimation, tooling design, machine selection, stock selection, and design reuse. Representative examples are illustrated below:
- 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).
Most users currently browse CAD models manually to locate similar parts. This is a very time consuming step and slows down the decision making process. Most product development engineers spend a lot of time searching for information. A search tool that can help in locating parts and assemblies having similar application-specific features will help in cutting down that time significantly and allow engineers to spend more time on creative aspect of their jobs. By improving decision making in design and planning functions, the shape similarity based search tool is expected to play an important role in reducing costs and reducing the time-to-market.
Technical Approach
The search tool locates existing parts similar to the new part based on some geometric attributes. It creates signatures for each of the parts in the database and stores the signatures along with the solid model of the part. A signature is a list of geometric attributes that describe the part and depends on the application. These pre-computed signatures reduce the time required for comparison and, thus, improve the speed of comparison. The search tool then uses the signatures to compare the signature of the query part with each of the signatures of the database parts to determine if the parts are similar.
We have developed two different techniques for performing search.
We have developed two different techniques for performing search.
- 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
The following papers provide more details on the above-described techniques.
- 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.
Contact:
Dr. Satyandra K. Gupta
Phone: 301.405.5306
Email: skgupta@umd.edu
Website: Dr. S. K. Gupta
