Mathematical modeling and FDM process parameters optimization using response surface methodology based on Q-optimal design

By O. Mohamed, Syed H. Masood, Jahar Bhowmik. 2016

183 citations recorded by the source corpus.

Abstract Fused deposition modeling (FDM) is a growing 3D printing technique widely practiced around the world in various industrial applications because of its ability to create complex 3D objects and geometries. Reduction of build time and feedstock material consumption without compromising the mechanical performance is the major concern in most industrial applications affecting the cost and the functionality of the manufactured part. One of the key issues of FDM process is how to select the correct parameters to reduce the build time and to reduce feedstock material consumption while maintaining high dynamic mechanical properties. In this study, influence of critical FDM parameters—layer thickness, air gap, raster angle, build orientation, road width, and number of contours—are studied using Q-optimal response surface methodology. Their effects on build time, feedstock material consumption and dynamic flexural modulus are critically examined. Mathematical models have been formulated to develop a functional relationship between the processing conditions and the process quality characteristics. Analysis of variance (ANOVA) technique was employed to check the adequacy and significance of mathematical models. Moreover, the optimal setting of process parameters was determined. A confirmation test was also conducted in order to verify the developed models and the optimal settings. The results show that Q-optimal design is a very promising method in FDM process parameter optimization. The results also confirm the adequacy of the developed models.

Subfields: Automotive Engineering, Industrial and Manufacturing Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/f98930e49f9739590408f6de39140213f3a47408

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

  1. M. Alsoufi
  2. A. E. Elsayed

In Industrial and Manufacturing Engineering

  1. M. Alsoufi
  2. A. E. Elsayed

In Mechanical Engineering

  1. M. Alsoufi
  2. A. E. Elsayed

Citations in the corpus