A multi-response parameters and tolerances concurrent optimization strategy, considering quality loss and manufacturing cost, is proposed to solve the problem of model parameter uncertainty. Firstly, multi-response quality loss function is developed based on model parameter uncertainty and the tolerances of design variables. Secondly, tolerance cost model is built according to experimental data, and then the concurrent optimization objective function of parameters and tolerance design is proposed. Optimal Pareto solutions for the optimal parameters and tolerances are obtained from multiobjective optimization algorithm, and onefactor multivariate analysis of variance is used to allocate tolerances. Finally, a practical example demonstrates that the proposed method not only can improve robustness and the performance of the model prediction, but also can maintain the optimal tradeoffs between quality loss and manufacturing cost. That is, the proposed method performs better than traditional methods on quality improvement and cost reduction.