TY - JOUR
T1 - Cyber coordinated simulation for distributed multi-stage additive manufacturing systems
AU - Sun, Hongyue
AU - Pedrielli, Giulia
AU - Zhao, Guanglei
AU - Zhou, Chi
AU - Xu, Wenyao
AU - Pan, Rong
N1 - Funding Information:
This work is partially supported by the NSF grants # CMMI-1846863, # CMMI-1829238, and Sustainable Manufacturing and Advanced Robotics Technologies, Community of Excellence (SMART CoE) at State University of New York at Buffalo.
Publisher Copyright:
© 2020 The Society of Manufacturing Engineers
PY - 2020/10
Y1 - 2020/10
N2 - 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.
AB - 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.
KW - Cyber coordination
KW - Discrete event simulation
KW - Freeze nano printing
KW - Multi-stage manufacturing
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U2 - 10.1016/j.jmsy.2020.07.017
DO - 10.1016/j.jmsy.2020.07.017
M3 - Article
AN - SCOPUS:85089526097
SN - 0278-6125
VL - 57
SP - 61
EP - 71
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
ER -