Statistical analysis tolerance using jacobian torsor model based on uncertainty propagation method


  • W Ghie



One risk inherent in the use of assembly components is that the behaviour of these components is discovered only at the moment an assembly is being carried out. The objective of our work is to enable designers to use known component tolerances as parameters in models that can be used to predict properties at the assembly level. In this paper we present a statistical approach to assemblability evaluation, based on tolerance and clearance propagations. This new statistical analysis method for tolerance is based on the Jacobian-Torsor model and the uncertainty measurement approach. We show how this can be accomplished by modeling the distribution of manufactured dimensions through applying a probability density function. By presenting an example we show how statistical tolerance analysis should be used in the Jacobian-Torsor model. This work is supported by previous efforts aimed at developing a new generation of computational tools for tolerance analysis and synthesis, using the Jacobian-Torsor approach. This approach is illustrated on a simple threepart assembly, demonstrating the method’s capability in handling threedimensional geometry.


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How to Cite

Ghie, W. (2009) “Statistical analysis tolerance using jacobian torsor model based on uncertainty propagation method”, The International Journal of Multiphysics, 3(1), pp. 11-30. doi: 10.1260/175095409787924472.