Study of Hardness and Compression Strength of Carbon Fibre Reinforced Poly-Lactic Acid Composites Fabricated by Fused Deposition Modelling Velammal Engineering College

Format:

Book

Conference/Event

Author/Creator:

Sugumar, Suresh, author.

Contributor:

Dhamodaran, Gopinath

Seetharaman, Pradeepkumar

Sivakumar, Rajkamal

Conference Name:

Automotive Technical Papers (2024-01-01 : Warrendale, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2024

Summary:

3-Dimensional (3D) printing is an additive manufacturing technology that deposits materials in layers to build a three-dimensional component. Fused Deposition Modelling (FDM) is the most widely used 3D printing technique to produce the thermoplastic components. In FDM, the printing process parameters have a major role in controlling the performance of fabricated components. In this study, carbon fibre reinforced polymer composites were fabricated using FDM technique based on Taguchi's Design of experimental approach. The matrix and reinforcement materials were poly-lactic acid (PLA) and short carbon fibre, respectively. The goal of this study is to optimize the FDM process parameters in order to obtain the carbon fibre reinforced PLA composites with enhanced hardness and compressive strength values. Shore-D hardness and compression tests were carried out as per American Society for Testing and Materials (ASTM) D2240 and ASTM D695 standards respectively, to measure the output responses. The FDM process parameters considered in this study are layer height, infill density and infill pattern. The grey relational analysis (GRA) based multi-response optimization technique is used to optimize the process parameters. Analysis of variance is used to determine the most influential process parameter. The results showed that 3D printed components with improved performance characteristics could be achieved at 0.1mm layer height, Grid shaped infill pattern, and 75g/cm3 infill density with a Shore-D hardness value of 76 and compressive strength of 42 N/mm2. It was identified that for multi-response optimization of equal weightage condition, the layer height contributed 44.44% followed by the contribution of Infill pattern and Infill density by 25.93% and 18.04% respectively. The developed regression model predicted the grade value at 90% confidence interval

Notes:

Vendor supplied data

Publisher Number:

2024-01-5227

Access Restriction:

Restricted for use by site license