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Progressive stamping is an important manufacturing process in making automotive parts. Springback and static loading performance are two critical concerns in the part development. An accurate FE-based prediction on springback and static loading performance could foresee and avoid costly pitfalls in future part development. A bracket, which has tight tolerance and loading performance requirement, is chosen for this study. Implicit and explicit solutions, two major algorithms for solving the FEM motion equations, are used to simulate progressive forming process, which is composed of rib embossing and multiple bending. The springback effect is predicted on the ‘part’ formed by both implicit and explicit solutions. Measurement on the physical part shows the implicit solution can provides a more accurate prediction on both the thickness and springback.

One type of TiO2 nanoparticles modified by stearic acid was prepared by sol-gel method and its structure was characterized using Laser Particle Analyzer (LPA) and Freeze-Etching Electron Microscopy (FEEM). To evaluate the benefits of the nanoparticles used as substitute for sulfurized olefins in gear oils, the tribological properties of a mixture of TiO2 nanoparticles with a S-containing additive in base oil were investigated using four-ball tribotester. The experimental results show that there are some synergistic effects between the two additives. In addition, the function mechanism of TiO2 nanoparticles in the tribological process was elucidated by the use of X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM).