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Research Article | Open Access

Optimization of machining parameters in drilling hybrid sisal-cotton fiber reinforced polyester composites

Nurhusien Hassen MohammedDesalegn Wogaso Wolla( )
Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia
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Abstract

Machining natural fiber reinforced polymer composite materials is one of most challenging tasks due to the material's anisotropic property, non-homogeneous structure and abrasive nature of fibers. Commonly, conventional machining of composites leads to delamination, inter-laminar cracks, fiber pull out, poor surface finish and wear of cutting tool. However, these challenges can be significantly reduced by using proper machining conditions. Thus, this research aims at optimizing machining parameters in drilling hybrid sisal-cotton fibers reinforced polyester composite for better machining performance characteristics namely better hole roundness accuracy and surface finish using Taguchi method. The effect of machining parameters including spindle speed, feed rate and drill diameter on drill hole accuracy (roundness error) and surface-roughness of the hybrid composite are evaluated. Series of experiments based on Taguchi's L16 orthogonal array were performed using different ranges of machining parameters namely spindle speed (600,900, 1200, 1600 rpm), feed rate (10, 15, 20, 25 mm/min) and drill diameter (6, 7, 8, 10 mm). Hole roundness error and surface-roughness are determined using ABC digital caliper and Zeta 20 profilometer, respectively. Optimum machining condition for drilling hybrid composite material (speed: 1600 rpm, feed rate: 25 mm/min and drill diameter: 6 mm) is determined, and the results are verified by conducting confirmation test which proves that the results are reliable.

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AIMS Materials Science
Pages 119-134

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Cite this article:
Mohammed NH, Wolla DW. Optimization of machining parameters in drilling hybrid sisal-cotton fiber reinforced polyester composites. AIMS Materials Science, 2022, 9(1): 119-134. https://doi.org/10.3934/matersci.2022008

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Received: 23 September 2021
Revised: 15 November 2021
Accepted: 17 November 2021
Published: 15 February 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)