Techno-economic modeling of 4D printing with thermo-responsive materials towards desired shape memory performance

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.