With the development of cloud computing technology, it shows unique advantages in high-performance computing applications. In this study, the cloud computing platform AWS was used to simulate and optimize the temperature field during arc additive manufacturing (AM) of 7055 aluminum alloy. The mathematical model of the temperature field is established by defining the thermal physical properties of the material and applying the Fourier heat conduction law and is solved by the finite element method and finite difference method. In the study, the temperature control strategy was optimized by adjusting parameters such as scanning speed, laser power, and cooling system, and the temperature gradient and maximum temperature in the manufacturing process were significantly improved. The results show that the model can effectively predict and control temperature change, and improve the manufacturing precision and material properties. This study demonstrates the application potential of cloud computing in complex industrial simulation and provides the theoretical basis and technical support for efficient arc additive manufacturing.