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

Abstract

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 1 , P 25 , and P 50 ) that allow 1, 25, or 50 machines to start heating, respectively. The trade-off analysis results show that P 25 can be preferred when a balance between cycle time and energy costs is pursued, while P 1 or P 50 can be chosen if either energy cost (with P 1 ) or cycle time (with P 50 ) 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.

Investigation of an Optimal Material Addition Rate for Energy Consumption and Dimensional Accuracy in Fused Filament Fabrication of CFR-PEEK

“…The resultant regression models of energy consumption show that the energy consumption of FFF for CFR-PEEK is expressed as a decreasing non-linear function of the MAR, as addressed in the existing studies. Indeed, process parameter combinations that lead to a short build time in this study show a high MAR and a resultant low energy consumption value in that the energy consumption of FFF for CFR-PEEK is significantly affected by printing time [ 14 ]. This energy behavior on the MAR is consistently observed in all the sample types, and the results support that an increase in AM process efficiency can greatly decrease the energy consumption of FFF for CFR-PEEK.…”

“…For each sample type, a full-factorial experimental design was planned to fabricate experimental samples by varying layer thickness and printing speed levels. These two FFF process parameters were chosen due to their significant effects on energy consumption and dimensional accuracy for CFR-PEEK outputs [ 14 , 16 , 24 ]. All possible combinations of layer thickness at five levels and printing speed at six levels were randomly organized for the experiments of each sample type (see Table 1 ).…”

“…As the role of AM has been emphasized to realize sustainable manufacturing, recent studies have investigated energy performance in FFF to understand energy behavior and optimal AM operations for energy savings [ 1 ]. A concept of the process rate (i.e., added material volume or mass per printing time) of FFF has been employed in recent studies to effectively model energy performance in FFF [ 11 , 12 , 13 , 14 ]. This paper refers to the process rate of FFF as the material addition rate (MAR).…”

“…Lunetto et al [ 13 ] derived regression models to predict the energy consumption of FFF using ABS and polycarbonate ABS on the MAR, and they claimed that the MAR is a comprehensive measure of complexity in FFF operations to effectively characterize the energy consumption of FFF. Hassan et al [ 14 ] employed a regression model of electric power demand on the MAR of FFF for CFR-PEEK, and they simulated manufacturing scenarios with different FFF machine quantities to analyze a trade-off between energy costs and cycle time. Kim et al [ 16 ] derived the regression models of power demand and energy consumption on the MAR of FFF for CFR-PEEK to simulate the energy performance of an AM system that handles multiple FFF machines and aircraft part designs.…”