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Abstract
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.
Data availability statement
The data that support the findings of this study are available from the corresponding author, Lin Li, upon reasonable request.
Additional information
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Notes on contributors
Muyue Han
Muyue Han is a PhD student in the Department of Mechanical and Industrial Engineering at the University of Illinois at Chicago, IL, USA. She received a BS degree in environmental engineering from DongHua University, Shanghai, China, in 2015, and an MS degree in environmental engineering from the University of California, Irvine, CA, USA, in 2018. Her research interests include additive manufacturing, shape memory materials, environmental sustainability, and economic analysis.
Yiran Yang
Dr. Yiran Yang is an assistant professor at the Department of Industrial, Manufacturing, and Systems Engineering at the University of Texas at Arlington, TX, USA. She received a BS degree in behicle engineering from Beijing Institute of Technology, Beijing, China, in 2013, an MS degree in mechanical engineering from Purdue University Northwest, IN, USA, in 2015, and a PhD degree in industrial engineering and operations research from the University of Illinois at Chicago, IL, USA, in 2019. Dr. Yang’s research is mainly focused on sustainability practices in advanced manufacturing and circular economy-driven additive manufacturing.
Lin Li
Dr. Lin Li is an associate professor and the Industrial Engineering Program Director in the Department of Mechanical and Industrial Engineering at the University of Illinois at Chicago, IL, USA. He also serves as the director of the U.S. Department of Energy Industrial Assessment Center and the director of the Sustainable Manufacturing Systems Research Laboratory at the University of Illinois at Chicago. He received a B.E. degree in mechanical engineering from Shanghai Jiao Tong University, Shanghai, China, in 2001, and an MSE degree in mechanical engineering, an MSE degree in industrial and operations engineering, and a PhD degree in mechanical engineering from the University of Michigan, Ann Arbor, MI, USA, in 2003, 2005, and 2007, respectively. His research interests include energy control and electricity demand response of manufacturing systems, environmental sustainability of additive manufacturing processes, cost-effective cellulosic biofuel manufacturing system, lithium-ion electric vehicle battery remanufacturing and reliability assessment, multi-machine system modeling and throughput estimation, and intelligent maintenance of manufacturing systems.