Abstract
Fused deposition modeling (FDM) is becoming the most promised additive manufacturing (AM) process in recent years due to the evident benefits, such as high design flexibility, low cost, friendly and economically use. The current study considers an optimization of four different FDM parameters varied in three levels, as layer thickness (0.17 mm, 0.25 mm and 0.33 mm), infill density (25, 50 and 75%), shell thickness (0.8 mm, 1.2 mm and 1.6 mm) and raster angle (0 degrees, 30 degrees and 60 degrees) with an objective to reduce printing time, part weight and to enhance flexural modulus using Polyethylene Terepthalate glycol modified (PET-G) material. Mono optimization of FDM input parameters has been done using signal to noise ratio method obtained from Taguchi's L(9)Orthogonal Array (OA) and multi response optimization is applied through Grey Relational Analysis (GRA) and technique of order preference similar to ideal solution (TOPSIS) techniques. The response or its criteria weightages are calculated using Shanon's entropy and CRITIC method which gives different weightages for the considered responses. Printing time ranks top with 37% from entropy method followed by flexural modulus with 36% and part weight ranks last with 28%.Flexural modulus ranks tops with 43% followed by part weight with 29% and printing time takes last position with 28% weightage through CRITIC method.The ranking of alternatives from GRA- entropy and GRA- CRITIC methods are similar by recommending A1B1C1D1 (0.17 mm layer thickness, 25% infill density, 0.8 mm shell thickness and 0 degrees raster angle) but TOPSIS-entropy and TOPSIS - CRITIC methods suggested different parameter combination A2B3C1D2 (0.25 mm layer thickness,75% infill density, 0.8 mm shell thickness and 30 degrees raster angle). From all the four different methods adopted for optimization, the parameter setting obtained from level total suggests A2B1C1D2 (0.25 mm layer thickness, 25% infill density, 0.8mm shell thickness and 30 degrees raster angle) and completely opposite to the ranking of alternatives. The carried - out confirmation trials carried out validated the optimized settings resulted from different methods. Infill density is found to be the most significant factor as compared to other input factors over the output assessed parameters