Optimization of Additive Manufacturing (Fused Deposition Modeling) of PLA Material Using TOPSIS Approach

Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly nature, affordability, and ease of processing. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) for PLA material using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The researchers performed experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including dimensional accuracy, surface finish, and mechanical properties. The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. The TOPSIS approach, a technique for making decisions based on multiple criteria, was used to analyze the experimental data and determine the best parameter settings. TOPSIS provides a comprehensive method for optimizing parameters in FDM by taking into account both the closeness to the ideal solution and the distance from the negative ideal solution. The results demonstrated the efficacy of the TOPSIS method in pinpointing the most advantageous parameter combinations for improving the printing quality and efficiency of PLA components. The optimization framework that has been developed offers valuable insights into the optimization and control of processes, thereby facilitating the wider implementation of FDM technology across different industries. This study enhances the comprehension of Fused Deposition Modeling (FDM) for Polylactic Acid (PLA) material and provides useful techniques for optimizing FDM parameters. Manufacturers can improve printing productivity, quality, and sustainability by utilizing the TOPSIS approach. This, in turn, will help promote the wider use of AM technology in various applications.