The crankshaft manufacturing process primarily comprises machining, single jacket, and double jacket stages. These stages collectively produce substantial carbon emissions, which significantly impact the environment. Low-carbon energy development and humanity's future are closely related. To promote the sustainable development of crankshaft manufacturing enterprises and improve the production efficiency of crankshafts, research on sustainable collaborative scheduling problems in multi-stage mixed flow shop for crankshaft components is conducted. In addition, the transportation process of related workpieces in the crankshaft manufacturing process, which generally have a large mass, also produces substantial carbon emissions. This paper constructs a multi-objective integer optimization model based on the manufacturing process characteristics of crankshaft components, with minimizing the maximum manufacturing time and carbon emissions as optimization objectives. Considering the complexity of the problem, a comprehensive algorithm integrating moth-flame optimization and NSGA-III is used to solve the mathematical model. Through case experiments, the integrated algorithm is compared and analysed with four classic multi-objective optimization algorithms: NSGA-III, NSGA-II, MOEA/D, and MOPSO. The experiments demonstrate that the algorithm presented in this paper offers significantly enhanced optimization efficiency in solving the problem under study compared to other algorithms. Moreover, this paper compares multi-stage collaborative scheduling and non-collaborative scheduling in the crankshaft manufacturing process, ultimately demonstrating that collaborative scheduling is more conducive to the sustainable development of manufacturing enterprises. The results indicate that the annual carbon emissions can reduce about 3.6 ton.
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