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http://dx.doi.org/10.1016/j.jcde.2016.04.002

A framework for similarity recognition of CAD models  

Zehtaban, Leila (University of Stuttgart)
Elazhary, Omar (University of Stuttgart)
Roller, Dieter (University of Stuttgart)
Publication Information
Journal of Computational Design and Engineering / v.3, no.3, 2016 , pp. 274-285 More about this Journal
Abstract
A designer is mainly supported by two essential factors in design decisions. These two factors are intelligence and experience aiding the designer by predicting the interconnection between the required design parameters. Through classification of product data and similarity recognition between new and existing designs, it is partially possible to replace the required experience for an inexperienced designer. Given this context, the current paper addresses a framework for recognition and flexible retrieval of similar models in product design. The idea is to establish an infrastructure for transferring design as well as the required PLM (Product Lifecycle Management) know-how to the design phase of product development in order to reduce the design time. Furthermore, such a method can be applied as a brainstorming method for a new and creative product development as well. The proposed framework has been tested and benchmarked while showing promising results.
Keywords
Design classification; Opitz coding system; Similarity retrieval;
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