As an important part of modern transportation, air transportation relies on aero-engines as its core power devices. Turbine blades, being the key components of aero-engines, have a complex manufacturing process with high precision requirements. However, current workshop practices rely on manual production scheduling, which struggles to solve the complex scheduling problems involving multiple processes, multiple pieces of equipment, and multiple tasks. To address these challenges, this paper introduce an intelligent production scheduling algorithm that can efficiently allocate complex tasks and optimize resource utilization. Tailored to the unique manufacturing characteristics of turbine blades, the algorithm incorporates parallel process optimization and multi-task batch processing. Moreover, we use functions such as giving priority to urgent orders, managing equipment status, and batch processing similar processes. Through comprehensive numerical results, the optimized production scheduling results demonstrate significant reductions in average waiting time and notable improvements in equipment utilization, affirming the algorithm’s effectiveness and practicality.