Cyber coordinated simulation for distributed multi-stage additive manufacturing systems |
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| Affiliation: | 1. Industrial Engineering, University at Buffalo, Buffalo, NY, 14260 USA;2. School of Computing Informatics & Decision Systems Engineering, Arizona State University, Tempe, AZ, 85251 USA;3. Alta Devices Inc. Sunnyvale, CA 94085 USA;4. Computer Science and Engineering, University at Buffalo, Buffalo, NY, 14260 USA;1. Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China;2. Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China;3. Green Fan Manufacturing Collaborative Innovation Center in Hubei Province, Wuchang Institute of Technology, Wuhan 430065, China;1. Department of Industrial & Manufacturing Engineering, University of Wisconsin - Milwaukee, Milwaukee, WI, USA;2. Lubar School of Business, University of Wisconsin - Milwaukee, Milwaukee, WI, USA;1. Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology De Zaale, 5600 MB, Eindhoven, The Netherlands;2. Equipment and Automation Technologies (E&A), Nexperia Jonkerbosplein 52, 6534 AB, Nijmegen, The Netherlands;1. Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA;2. School of Engineering Design and Professional Programs, Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA;1. Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science & Technology, Wuhan, 430081, China;2. Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science & Technology, Wuhan, 430081, China;3. School of Engineering, Deakin University, Geelong, Victoria, 3216, Australia;4. Department of Computing, Engineering and Mathematics, University of Brighton, Brighton, BN2 4GJ, United Kingdom |
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| Abstract: | Additive Manufacturing (AM) processes have been increasingly used to manufacture energy storage products with dedicated material preparation and post-processing stages to enhance product properties. Most researchers focus on selecting materials and improving processes, yet the system modeling and management has not been investigated so far. This paper extends the conventional single-stage AM processes to multi-STage distRibutEd AM (STREAM) systems. In STREAM, a batch of material produced at the pre-processing stage is jointly consumed by distributed AM printers, and then the printed parts are collected for the post-processing stage. Modeling and managing such complex systems have been challenging. We propose a novel framework for “cyber-coordinated simulation” to manage the hierarchical information in STREAM. This is important because simulation can be used to infuse data into predictive analytics, thus providing guidance for the optimization and control of STREAM operations. The proposed framework is hierarchical in nature, where the single-stage, multi-stage, and distributed productions are modeled through the integration of different simulators. We demonstrate the proposed framework with simulation data from Freeze Nano Printing (FNP) AM for the fabrication of energy storage products. |
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| Keywords: | Freeze nano printing Discrete event simulation Cyber coordination Multi-stage manufacturing |
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