This work presents a complete methodology for the analysis of forming processes that involve large material deformations. These processes are applied in the manufacturing of mechatronic brake systems to ensure optimal joint sealing and system performance. In the past, expensive trial- error experimental campaigns were required to achieve optimal designs. With the development of computational methods in product design and engineering, those costly, high-time consuming procedures, have been effectively replaced by virtual prototyping. In the present work a hybrid computational simulation technique, combining Element-Free Galerkin and Finite Element methods, has been developed for the modeling of different forming processes between dissimilar metals. Joining techniques include casing and direct part deformation to create solid joints. After simulation of the forming process, successive simulation steps follow for the analysis of the system performance under different mechanical - thermal load cases, including temperature, differential fluid pressure and cyclic loading, therefore considering the effect of work hardening in the materials forming the joint. Mesh adaptivity, remeshing and other meshing techniques allow for accurate reproduction of high deformation behavior while maintaining computation efficiency. The obtained results show good correlation in terms of deformed shapes and joining forces between numerical and experimental results. The methodology supports studies of load cases, helps for the geometric design of sealing valves and predicts cross-sectional profiles accurately. However, it is computationally intensive due to the use of remeshing functionalities, which are necessary to accurately model the large deformations that occur in the forming process and does not account for material damage modelling. Despite these limitations the methodology offers high accuracy and adaptability to different geometries and shows potential to reduce the need for experimental testing. It has proven to be a valuable tool in optimizing manufacturing design.