Statistical analysis and multi-criteria optimization of fused deposition additive manufacturing process for acrylic butadiene styrene parts

Abstract

The current market trend and customer requirement are to find excellent quality products within shortest manufacturing time. Therefore, it is essential to analyze the processing conditions that affect the product’s quality before the actual manufacturing of the product. This study aims to experimental analysis and multi-criteria optimization of fused deposition additive manufacturing (FDAM) process for differently shaped acrylic butadiene styrene material parts. Five process variables such as raster angle, infill density, layer thickness, nozzle temperature and print head speed are considered which vary at three levels. A total of 33 experiments have been designed based on central composite design method. The surface roughness, manufacturing time and improved dimensional accuracy are considered as the response parameters in this study. Mitutoyo SJ-410 roughness tester, stopwatch and electronic digital Vernier caliper gauge are used to record the surface roughness, manufacturing time and dimensional variation, respectively. The multi-criteria optimization was performed through the technique for order of preference by similarity to ideal solution (TOPSIS) and Grey relational analysis (GRA) techniques. Concerning TOPSIS, the improvement in responses are obtained as, surface quality of concave (Racc) 8.85%, convex (Racv) 18.43%, manufacturing time (MT) 11.11%, dimensional improvement in length (δl) 1.60%, width (δw) 0.47% and height (δh) 0.46%. Similarly, the improvement found in same responses through GRA approach are Racc 7.85%, Racv 10.34%, MT 7.69%, δl 10.05%, δw 6.50% and δh 28.20%, respectively. The experimental results show that, the optimized parameters provide up to 18.43% improvement in surface quality, 11.11% saving in manufacturing time with a significant reduction in dimensional variation. The findings of this study will help the designers of functional parts to improve the quality of designed product.