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Most fixture design process are based on the reuse of the previous design knowledge and experience, in this paper, we use a case-based design (CBD) method to design fixture. Based on the analysis of various CBD methods, we found that most methods used to calculate the similarity between new part and cases are too single, so we put forward a method combining the semantic attribute similarity and the shape similarity together, use a weighted algorithm to calculate the similarity. Using this method, we designed a Fixture Design System on CATIA V5 R19, and use this system to retrieve and design fixture, the retrieved results are more close to the new part and reusable, the design process is more efficient.

In the assembly design process of aircraft products, plenty used standard parts make it boring and difficult to extract assembly features and assembly constraints between the products and standard parts.Therefore,in this paper, the practical methodology for light-weight of the tree-dimensional model for rapid assembly and the automatic determination for specification of the parts are proposed. Eventually the assembly for the standard parts can be implemented rapidly, intelligently, in batch, and automatically.

Automatic generation of manufacturing setup planning is studied in this work. The mathematical model to describe the tolerance information and datum-machining feature relationship has been formulated based on extended graphics. By means of the transformation between the feature tolerance relationship graph(FTG) and the datum-machining feature relationship graph (DMG), the algorithm to automatically generate setup planning has been given based on the tolerance analysis and manufacturing resources capability model. The algorithm can identify the machining feature and datum, optimize setup groups based on the manufacturing resource capability and tolerance analysis, as well as minimize the influence of the locating error stack-up on the machining quality. Finally, a case study of setup planning is presented to verify the feasibility of the methodology.