Influence of Process Parameters on Tensile Strength of Additive Manufactured PLA Parts using Taguchi Method
Y. Venkata Narayana1, N Pruthvi Reddy2

1Dr. Y.Venkata Narayana, Professor, Sreenidhi Institute of Science and Technology, Hyderabad.
2N Pruthvi Reddy, M.Tech student, Sreenidhi Institute of Science and Technology, Hyderabad.

Manuscript received on 20 August 2019. | Revised Manuscript received on 25 August 2019. | Manuscript published on 30 September 2019. | PP: 7635-7639 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6191098319/2019©BEIESP | DOI: 10.35940/ijrte.C6191.098319

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Influence of layer thickness nozzle temperature and angle on tensile strength of PLA fabricated with FDM (FFF) was experimentally investigated. Polylactic Acid (PLA) is a semi-crystalline and bio-friendly thermoplastic polymer has identified as important material in different applications due to its mechanical characteristics. Fused Deposition Modeling (FDM) is a one of the proved technology in Fused Filament Fabrication (FFF) technique in additive manufacturing process. In present investigation different specimens were fabricated using FDM technique with different layer height and different layer angles for finding influence of these manufacturing parameters on tensile strength of the specimen. Specimens were fabricated and tested as per ASTM D638 standard. It is clearly observed that tensile strength is more for +450/-450 layer angle than the +00/-00 layer angle for a given layer height(h=0.10 mm, h=0.15mm and h=0.20mm).The TAGUCHI analysis is carried with nozzle temperature, layer thickness and angle finding optimal values. It has been observed that, the optimal parameter is angle, which is equal to 300.the ANOVA variation of angle layer with tensile strength has been observed that 18.10-31.90.
Keywords: Specimen Preparation, 3D-Printing, Testing Machine, Orthogonal Array, TAGUCHI Analysis, ANOVA.

Scope of the Article:
Machine Learning