Analysis and Simulation of Energy Performances of Additive Manufacturing Systems

Additive manufacturing (AM) is an evolving technology that offers distinct advantages over conventional subtractive manufacturing by fabricating a variety of complex-shaped parts with mass customization. Selective laser melting (SLM), electron beam melting (EBM), and fused filament fabrication (FFF) are popular AM processes. A recent growing trend in AM suggests the necessity of an energy study to explore energy performance measures. In this research, a comprehensive energy study is performed for various AM processes with three objectives. The first objective of this study is to assess relationships between energy performance measures and two key process parameters (infill patterns and infill percentages) for FFF. This study proposes a full factorial experimental design to estimate both individual and combined effects of infill patterns and infill percentages on energy performances of FFF. The findings from this study demonstrate that energy performances can be controlled by adjusting the FFF process parameters to improve both operational and sustainability performance. The second objective of this study is to develop an energy simulation tool as a useful application of FFF energy studies to evaluate the energy performance of AM facilities. An energy simulation method is proposed to use a power model with material addition rates (MAR) estimated from process parameters of FFF experiments. Also, a control strategy is proposed to attain the balanced combination between performance measures based on the trade-off analysis. Results of this study show that balanced energy costs and cycle times would be obtained by controlling the number of FFF machines to work during printing relatively small-sized parts. The third objective is to conduct a comparative energy simulation study for the frequently used AM technologies (SLM, EBM, and FFF) with the simulation approach. The simulation model proposed in the second objective is further used to evaluate the energy performances of SLM, EBM, and FFF processes. Also, a trade-off between electricity costs and average cycle time is performed to identify balanced sets of performance measures for SLM, EBM, and FFF systems. Results of this study can help industrial practitioners lower electricity costs by maintaining the acceptable productivity level in facilities that run various AM processes