With increasingly stringent carbon policies, the development of traditional heavy industries with high carbon emissions has been greatly restricted. Manufacturing companies surveyed use multifunctional machining machines and variable speed cranes, as the lack of rational planning results in high energy wastage and low productivity. Reasonable scheduling optimization is an effective way to reduce carbon emissions, which motivates us to work on this research. To reduce the comprehensive energy consumption of the machining process and transportation process in an actual manufacturing environment, this paper addresses a new low-carbon scheduling problem of flexible manufacturing and crane transportation considering multi-state collaborative configuration (LSP-FM&CT-MCC). First, an integrated energy consumption model based on multi-state machining machines and cranes is established to optimize the overall energy efficiency of the production process. Then, a new hybrid differential evolution algorithm and firefly algorithm with collaborative state optimization strategy (DE-FA-CSOS) is proposed to solve the proposed MIP model. In DE-FA-CSOS, the differential evolution algorithm (DE) is used for global search, and the firefly algorithm (FA) is used for local search. The collaborative state optimization strategy (CSOS) is proposed to guide the search direction of the DE-FA algorithm, which greatly improves the performance of the hybrid algorithm. Finally, the practicality and superiority of the solution method are verified by examples. The results show that machining and transportation energy consumption is reduced by 25.17% and 34.52%, respectively. In the context of traditional optimization methods and manual scheduling modes facing failure, the method has a broad application background for manufacturing process optimization in such workshops, which is of guiding significance for promoting the low-carbon development of traditional heavy industry manufacturing.