Experimental investigation and multi-objective optimization of FDM process parameters for mechanical strength, dimensional accuracy, and cost using a hybrid algorithm

Abstract

Considering many advantages of 3D printing of polymers using Fused Deposition Modeling (FDM) technique and its service nature, achieving maximum customer satisfaction is very important. The satisfaction of each particular customer may be obtained by providing one or more different outputs of this process, which may not have the same weights. This paper concentrates on multi-objective optimization of three response variables, including tensile strength, dimensional accuracy, and production cost. Eight FDM process parameters containing orientation, layer thickness, infill density, nozzle temperature, print speed, number of shells, infill pattern, and print position have been selected. For carrying out experimental studies, specimens were designed based on Taguchi L27 and manufactured according to ASTM D368-( Ⅰ ) using Polylactic Acid (PLA). Then the signal-to-noise ratio is calculated, and the mathematical regression model of all outputs is obtained. Finally, an intuitive optimal Pareto front is presented to the customer rather than a single point. By repeating the proposed algorithm for eight other customers, the average satisfaction number of 88.56% indicates the efficiency of this method.