Copper–tin alloys are widely used in the machining and molding of sleeves, bearings, bearing housings, gears, etc. They are a material used in heavy-duty, high-speed and high-temperature situations and subject to strong friction conditions due to their high strength, high modulus of elasticity, low coefficient of friction and good wear and corrosion resistance. Although copper–tin alloys are excellent materials, a higher performance of mechanical parts is required under extreme operating conditions. Plastic deformation is an effective way to improve the overall performance of a workpiece. In this study, medium-temperature compression tests were performed on a semi-solid CuSn10P1 alloy using a Gleeble 1500D testing machine at different temperatures (350−440 °C) and strain rates (0.1−10 s−1) to obtain its medium-temperature deformation characteristics. The experimental results show that the filamentary deformation marks appearing during the deformation are not single twins or slip lines, but a mixture of dislocations, stacking faults and twins. Within the experimental parameters, the filamentary deformation marks increase with increasing strain and decrease with increasing temperature. Twinning subdivides the grains into lamellar sheets, and dislocation aggregates are found near the twinning boundaries. The results of this study are expected to make a theoretical contribution to the forming of copper–tin alloys in post-processing processes such as rolling and forging.

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The application of semi-solid metal forming technology to the production of high-quality copper alloy parts has attracted more and more attention. Accordingly, as the key and foundation of semi-solid metal forming technology, it is particularly important to stably and efficiently prepare copper alloy semi-solid slurry with high quality. The purpose of this study was to innovatively optimize the process parameters by combining multiple optimization algorithms to stabilize the preparation of high-quality CuSn10P1 semi-solid slurry. And the self-developed Fully Enclosed Melt-Constrained Cooling Inclined Plate (FEMCIP) device was taken as the experimental equipment. Based on the optimization method of neural network genetic algorithm, the parameters of the preparation process of CuSn10P1 semi-solid slurry were optimized by combining orthogonal experimental design, grey correlation analysis method and Latin hypercube sampling, and using the finite element analysis software ProCAST and data analysis software MATLAB with the average shape factor as the evaluation index. By comparing with the slurry before optimization, numerical simulation results and experimental verification results, it was found that the semisolid slurry prepared by the crucible with preheating temperature of 990°C, cooling water flow rate of 680.517 L/h, cooling channel angle of 45°, inclined plate length of 300 mm and quasi-isothermal time of 42.715 s had the best quality. In this research, the semi-solid slurry of CuSn10P1 alloy with uniform microstructure and high roundness of solid particles was prepared by using this optimization method, which provided a new optimization strategy for the preparation of semi-solid metal slurry by using inclined plate type equipment.