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SpaceX
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NASA
СпутникиРНSpaceXРоскосмосNASAGreen product design is a key approach to achieving sustainable manufacturing. In the design process, the complex dependencies among function, structure, materials, and processes, along with the influence of multidimensional constraints, directly affect the optimality and feasibility of design solutions. To address this, this paper proposes a dual layer network (DLN) model to explicitly describe the hierarchical dependencies among function, structure, materials, and processes, while representing the impact of constraints on design decisions in a separate constraint layer. Based on this model, a constraint-driven heuristic search method is introduced to generate an initial population that satisfies the constraints. Bayesian optimization is then applied to identify the design solution with the lowest environmental impact. A case study on a 2.5 MW wind turbine is conducted to validate the proposed method. The results demonstrate that the DLN model effectively supports green design optimization for complex products, improving both environmental sustainability and feasibility.
Green product design is a key approach to achieving sustainable manufacturing. In the design process, the complex dependencies among function, structure, materials, and processes, along with the influence of multidimensional constraints, directly affect the optimality and feasibility of design solutions. To address this, this paper proposes a dual layer network (DLN) model to explicitly describe the hierarchical dependencies among function, structure, materials, and processes, while representing the impact of constraints on design decisions in a separate constraint layer. Based on this model, a constraint-driven heuristic search method is introduced to generate an initial population that satisfies the constraints. Bayesian optimization is then applied to identify the design solution with the lowest environmental impact. A case study on a 2.5 MW wind turbine is conducted to validate the proposed method. The results demonstrate that the DLN model effectively supports green design optimization for complex products, improving both environmental sustainability and feasibility.
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School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
Jing Guo, Jin Qi & Jie Hu
School of Mechanical Engineering, Shandong University, Jinan, 250061, China
Liming Wang
Authors
Correspondence to Jing Guo.
School of Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, China
Jianrong Tan
School of Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, China
Zhenyu Liu
Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, China
Weifei Hu
© 2027 The Chinese Mechanical Engineering Society
Guo, J., Qi, J., Hu, J., Wang, L. (2027). A Dual Layer Network Model for Green Design Optimization. In: Tan, J., Liu, Z., Hu, W. (eds) Advances in Mechanical Design. ICMD 2025. Mechanisms and Machine Science, vol 206. Springer, Singapore. https://doi.org/10.1007/978-981-95-7904-4_101
Download citationDOI: https://doi.org/10.1007/978-981-95-7904-4_101
Published: 25 June 2026
Publisher Name: Springer, Singapore
Print ISBN: 978-981-95-7903-7
Online ISBN: 978-981-95-7904-4
eBook Packages: Mechanical Engineering (R0)Springer Nature Proceedings excluding Computer Science