Large and thick aeronautical structural parts frequently exhibit significant distortions after machining because of the residual stresses generated along the manufacturing process. A post-machining shape correction phase, called reshaping, has to be applied to each part before proceeding to the assembly stage. At the moment this process relies entirely on the know-how and experience of a specialized operator. As a consequence, the process is expensive and time-consuming. Therefore, there is a need at an industrial level to solve this problem with the support of numerical simulation tools. However, to reach this target, it is required to explore beforehand the input space to construct a solution dictionary in order to provide real-time response. Both requirements oblige to launch a multi-parametric analysis under a Model Order Reduction (MOR) framework. A complete reshaping process consists of a sequence of elementary operations, among which bending straightening is selected in its three-point bending configuration and it is simulated by applying the Sparse Subspace Learning method (SSL). By using the MOR approach, new insights for the distortion mitigation via plastic bending can be explored that will help to understand the open problem of reshaping.

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