An integrated setup/fixture planning approach for machining prismatic parts

Abstract

Setup/fixture planning for machining prismatic parts is usually carried out by grouping features/operations into setups, determining suitable locating surfaces for each setup, and sequencing setups and operations in each setup. The presently developed setup/fixture planning methods can be classified into three categories: multi-constraints, fixture driven, and tolerance analysis planning methods. The multi-constraints planning is theoretically sound, but very difficult to use. In fixture driven planning, the generated setup plans are highly practical, but may not be optimal. Tolerance analysis based planning cannot be used to generate the optimal solution by itself. In this research, a new integrated setup/fixture planning approach is developed to identify the optimal and practical setup/fixture plan. The planning is conducted in four steps. (1) The dissimilarity degree matrix (DDM), operation precedence graph (OPG), and hybrid graph are used to describe the requirements and constraints for setup/fixture planning. (2) A setup precedence graph (SPG) is used to describe precedence constraints between setups. The SPG is generated by the vertex clustering algorithm. Precedence loops among setups are avoided by checking whether two serial vertex clusters can generate a loop. (3) Suitable locating surfaces are selected for each setup in a SPG. When the fixture locating surface and design datum surface are different, two types of dimension recalculations are employed to obtain the dimensions against the locating surfaces. (4) All the candidate setup/fixture plans are evaluated based on the number of setups and recalculation of dimensions. An example is given to demonstrate the effectiveness of the developed approach.

Keywords:

• setup/fixture planning
• hybrid graph
• setup precedence graph
• locating surfaces

Acknowledgements

The project was supported by the Science and Technology Innovative Activity Program, Shanghai (No. 09dz1124600), National High-Tech. R & D Program for CIMS, China (No. 2007AA04Z140), the Research Fund for Doctoral Program of Higher Education, China (No. 20070248020) and National Natural Science Foundation, China (No. 50375097). Support of a Short Visit Grant for Foreign Scholars from the Ministry of Education, China is also acknowledged.