Tolerance-cost optimization for multi-cabin spacecraft assembly considering form errors

Tolerance-cost optimization plays an important role in trade-off between deviation reduction and manufacturing cost. However, very few studies focus on the assembly accuracy of the cabin using a more efficient tolerance allocation considering both quality and cost issues. Therefore, this paper proposes a tolerance-cost optimization method for multi-cabin assembly of spacecrafts based on the cloud model based genetic algorithm (CGA). To improve the accuracy of tolerance analysis, a comprehensive assembly accuracy analysis method is used, composed of tolerance representation and propagation. For tolerance representation, skin model shape and small displacement torsor theory are used to respectively represent the form and position errors. For tolerance propagation, the integrated Jacobian-skin model shapes model is used to compute the accumulative results of deviation. Simulation results demonstrate the capability of the proposed method to predict the assembly accuracy of cabins with non-ideal surfaces. To improve the efficiency of the optimization, CGA is utilized as an optimization technique. Compared with traditional optimization methods, simulation analysis shows superior performance of parameter optimization in the problem of tolerance-cost optimization of multi-cabin spacecraft.