Process optimization to improve surface finish in fused deposition modeling

Adnan, Nor Farahin Aida (2018) Process optimization to improve surface finish in fused deposition modeling. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Nowadays, fused deposition modeling (FDM) is one of the famous technique in additive manufacturing addictive manufacturing (AM) technologies. Fused deposition modeling (FDM) is one of the methods under rapid prototyping (RP). Rapid prototyping (RP) and rapid tooling (RP) is widely used in development and creating part. In this process, it will done layered by layered where it is known as layered manufacturing (LM). For this process, a few materials usually used such as Acrylonitrile Butadiene Styrene (ABS), polycarbonate (PC), ULTEM 9085 and lastly is Polyphenylsulfone (PPSU). Then, in process of creating this prototype in Fused Deposition Modeling (FDM), the material will be used is ABS due to it is price that affordable and easy to get while the other materials sometimes more expensive compare to ABS. Besides, ABS also has the same strength and hardness despite it is cheaper. The quality of prototype fabricated from FDM is depending on different process parameters of FDM process. Thus, this project will be focus on the process parameter in order to obtain excellent surface finish for prototype and observe the effect of the parameter on surface finish of the prototype. The results can be obtained by using Taguchi method and Analysis of Variance (ANOVA). The total number of experiment is 9 experiments using the Taguchi. The trapezium shaped of ABS printed was created by using SolidWorks software. From the experiment, the value of optimum parameter choose based on the S/N ratio graph are speed of deposition (100mm) , top infill (15%) and fill density (100%) . Meanwhile, the dominant factor that affected the surface finish is fill density and followed by speed of deposition and top infill. The best Ra value for 3 different parts are RaH (1.560 μm), RaV (13.810 μm) and lastly, for RaS (14.670 μm) respectively Last but not least, the percentage of error between predicted value and experimental value is 0.41 % which is acceptable due to the value is below than 10%.

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