Techno-economic modeling of 4D printing with thermo-responsive materials towards desired shape memory performance
建立了基于甲基丙烯酸酯热响应聚合物的4D打印技术经济模型，量化了成本与材料固化化学及形状记忆性能的关系，通过非线性优化实现单件总成本降低22.25%，并识别出原材料单价和操作员时薪为主要成本驱动因素。
Four-dimensional (4D) printing enables the fabrication of smart materials with self-adaptations of shapes and properties over time in response to external stimuli, indicating potential applications in numerous areas such as aerospace, healthcare, and automotive. Evaluating the techno-economic feasibility is key to enhancing the technology readiness level of 4D printing. In the current literature, studies have been conducted to understand the 3D printing process mechanism and associated cost; however, they are not applicable to 4D printing due to the much-increased complexity of the intercorrelated relationships between material compositions, process parameters across multiple stages, the stimuli-response mechanisms along the added time dimension, and 4D printing cost. In this research, a techno-economic model is established to quantify the cost of 4D printing with methacrylate-based thermo-responsive polymers, embedded with explicit relations between cost and the material solidification chemistry and shape memory properties. A nonlinear optimization problem is formulated, resulting in a set of process parameters that can lead to a 22.25% cost reduction in total cost per part without sacrificing the desired shape memory performance. A sensitivity analysis is conducted to investigate market-dependent and operator-oriented parameters in 4D printing. Two primary cost drivers are identified, i.e., the raw material unit price and the operator’s hourly rate.