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Simulating energy consumption based on material addition rates for material extrusion of CFR-PEEK: a trade-off between energy costs and cycle time. | LitMetric

Simulating energy consumption based on material addition rates for material extrusion of CFR-PEEK: a trade-off between energy costs and cycle time.

Int J Adv Manuf Technol

Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Yongin-si, 17104 Republic of Korea.

Published: March 2022

While many studies for material extrusion-based additive manufacturing (AM) of polymers focus on experimental approaches to evaluate relevant performance measures from process parameters, there is a lack of discussion to connect experimental results with useful applications. Also, one of the major deficiencies in the application literature is a trade-off analysis between energy costs and cycle time (time to produce an item from the beginning to the end) since improving these two measures simultaneously is challenging. Thus, this paper proposes an energy simulation method for performing a trade-off analysis between energy costs and cycle time using combinations of major AM process parameters for material extrusion. We conduct experiments using carbon fiber-reinforced poly-ether-ether-ketone (CFR-PEEK), which is increasingly used in material extrusion. From experimental results, we build a power model in which power (kW) is derived as a linear function of material addition rates (MAR). This MAR regression model is then used in a proposed simulation model that integrates discrete event simulation and numerical simulation. In our simulation case study of 50 machines and 40 scenarios, we investigate trade-offs between energy costs and cycle time with three control policies (P, P, and P) that allow 1, 25, or 50 machines to start heating, respectively. The trade-off analysis results show that P can be preferred when a balance between cycle time and energy costs is pursued, while P or P can be chosen if either energy cost (with P) or cycle time (with P) is more important than the other measure. Moreover, we find that the machine utilization, variability, and product volume have significant effects on energy costs and cycle time.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933047PMC
http://dx.doi.org/10.1007/s00170-022-08967-xDOI Listing

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