Multi-Objective Optimization of Selective Laser Melting Processes for Minimizing Energy Consumption and Maximizing Product Tensile Strength

As a sustainable manufacturing technology, selective laser melting (SLM) is a typical additive manufacturing (AM) method with high flexibility and material efficiency. However, SLM is intrinsically energy-intensive than conventional machining processes. By contrast, part quality, especially the tensile strength, is critical for applying SLM technology. Therefore, this study aims to minimize the process energy consumption and maximize the part tensile strength by optimizing three essential process parameters, namely laser power, scan speed, and overlap rate. First, single track and single layer experiments are applied to determine the constraints of process parameters. Then, analytical and statistical models are used to calculate energy consumption and part tensile strength. Finally, the process parameters to achieve compromised optimal solutions are located using the nondominated sorting genetic algorithm II (NSGA-II). A case study of a waveguide part manufactured via the SLM process is employed to demonstrate the effectiveness of the proposed approach. Results showed that both energy consumption and part tensile strength could be improved moderately using the proposed method. This study can potentially guide the process parameter selection for new material AM processes and improve the AM product quality.