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Integration of taguchi-grey relational analysis technique in parameter process optimization for rice husk composite


Citation

Nor Mohamed, Sity Ainy and Zainudin, Edi Syams and Salit, Mohd Sapuan and Md Deros, Mohd Azaman and Tajul ariffin, Ahmad Mubarak (2019) Integration of taguchi-grey relational analysis technique in parameter process optimization for rice husk composite. BioResources, 14 (1). pp. 1110-1126. ISSN 1930-2126

Abstract

Injection molding is a widely used manufacturing process operation that generates polymer products. The selection of optimal injection molding process settings is essential due to the distinct influences of process parameters on polymeric material behavior and quality, particularly during the injection process. Therefore, it is vital to determine the optimized process parameters to enhance the mechanical properties of the products and ensure the most favorable performance. This paper examined the integration of Taguchi’s method with grey relational analysis (GRA) to determine the effects of varied injection molding parameters on the mechanical properties such as tensile strength and hardness values. The experiments were designed using Taguchi’s L9 orthogonal array after weighing in control factors, such as melting temperature, injection pressure, injection speed, and cooling time. The GRA revealed that the multiple responses correlation was successfully established. Finally, an analysis of variance was performed to validate the test outputs. The results revealed that the most influential factor was injection pressure, sequentially followed by melting temperature, cooling time, and injection speed.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Institute of Tropical Forestry and Forest Products
DOI Number: https://doi.org/10.15376/biores.14.1.1110-1126
Publisher: Elsevier
Keywords: Integration; Injection molding; Natural composite; Optimization
Depositing User: Azhar Abdul Rahman
Date Deposited: 20 Oct 2020 19:13
Last Modified: 20 Oct 2020 19:13
Altmetrics: http://altmetrics.com-details.php?domain=psair.upm.edu.my&doi=10.15376/biores.14.1.1110-1126
URI: http://psasir.upm.edu.my/id/eprint/80288
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