Journal of Engineering in Industrial Research

h-index: 18     i10-index: 25

Optimization of Process Parameters Using Taguchi and ANOVA

Document Type : Original Research Article

Authors

Asnakew Sewale Belay 1
Fantahun Getie Tsegaw 2
Sisay Geremew Gebeyehu 2

1 University of Gondar, Gondar, Ethiopia

2 Faculty of Mechanical and Industrial Engineering, Bahir-Dar Institute of Technology, Bahir-Dar University, Bahir-Dar, Ethiopia

https://doi.org/10.48309/jeires.2024.212593
Abstract
The use of the best operating parameters is needed to produce better quality of plastic products. Since the quality of products is mostly influenced by process condition, determining the optimum process condition with a few experiments is a key task. Melting temperature, injection pressure and cooling time with three levels each were selected which directly affect the dimensional shrinkages in injection molding process of beverage crate product. Shrinkage is chosen as a response variable since it is cause of many defects. Taguchi method was selected for the optimization of these parameters. The objective of this research is to reduce the shrinkage of a crate. Nine types of crates were produced using Taguchi design of experiment (L9) approach. Minitab statistical software package were used to analyze experimental results. The shrinkage defects are the “smaller the better S/N ratio” type of quality characteristics. Significant parameters were identified through ANOVA at 95% confidence level. Optimal values for melting temperature, injection pressure and cooling time were found 290 C, 130 MPa, and 60 seconds, respectively. From analysis of variance, melting temperature was the most significant factor (14.7 %), cooling time was the second (11.5 %) and injection pressure was the least significant (9 %). The predicted optimum response variable (shrinkage) was found as 6.30 mm and the conformation experimental test gave 6.11mm. The margin error of 3% supported the acceptance of the confirmation test result of 6.11 mm. The shrinkage is reduced from 6.81 mm to 6.11 mm which is a 10.3% reduction. The identification of the influence of parameters is believed as a key factor in assisting injection molding process designers in determining optimum process conditions. Therefore, the implication of this research is that robust optimization approach withstands the injection molding process variations in a more realistic way.

Keywords

Taguchi
Design of experiment
Shrinkage
Injection molding
ANOVA
S/N

Subjects

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©2024 The author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit: http://creativecommons.org/licenses/by/4.0/

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Journal of Engineering in Industrial Research
Volume 5, Issue 3
Summer 2024
Pages 152-162

  • Receive Date 17 November 2024
  • Revise Date 26 November 2024
  • Accept Date 28 December 2024

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