Health & Environmental Research Online (HERO)


Print Feedback Export to File
6609615 
Book/Book Chapter 
Fused Deposition Modelling and Parametric Optimization of ABS-M30 
Cherkia, H; Kar, S; Singh, SS; Satpathy, A 
2020 
Springer Science and Business Media Deutschland GmbH 
Advances in Materials and Manufacturing Engineering. Proceedings of ICAMME 2019. Lecture Notes in Mechanical Engineering 
1-15 
English 
In the current development of generative manufacturing industries, 3D printing technologies have a significant impact in the production of complex geometry with least time and the absence of human intercession, tools, fixtures and dies. Presently in engineering application, fused deposition modelling (FDM) has better demand in additive manufacturing. The improvement in design quality and manufacturing in FDM is based on the proper selection of principal operational parameters. This paper experimentally describes the influence of stereotypical operational variables, i.e. layer thickness, raster angle, raster width, part build orientation and their reciprocation on the precision of change in length, width, thickness, hole diameter and angle orientation of test part of acrylonitrile butadiene styrene-M30 (ABS-M30) after generated by FDM approach. It was profound that shrinkage predominates along the diameter of hole but an increase in dimension of length, width, thickness and angle of inclination is more than the thirst value of the fabricated specimen. The most favourable parametric combination is followed to optimize the precise responses just as a change in length, width, thickness, hole diameter and angle orientation of build part by using a parametric design of Taguchi's L9 orthogonal array. As Taguchi's methodology is not much satisfactory for steady optimal factor amalgamation of each response Grey-Taguchi methods used to investigate the influence of FDM parameters on multi-performance characteristics, combining all the responses into a single response. The correlative effect of significant factors is determined by Analysis of Variance (ANOVA). Finally, the ANOVA on Grey relational grade indicates layer thickness, part build orientation and raster width which are significant. Layer thickness is the most influencing factor for part build. The percentage errors are 12.05, 4.55, 2.45, 3.4, 5.07 and 0.74 for change in length, width, thickness, diameter, angle and Grey relational grade, respectively. 
3D printing; Acrylonitrile butadiene styrene-M30 (ABS-M30); Analysis of Variance (ANOVA); Fused deposition modelling (FDM) 
Mishra, P. C.