A Comparative Bibilometric Analysis of Taguchi-Centered Optimization in Plastic Injection Moulding

Authors

  • S. E. S. Bariran Centre for Advanced Mechatronics and Robotics, College of Engineering, Universiti Tenaga Nasional
  • K. S. M. Sahari Centre for Advanced Mechatronics and Robotics, College of Engineering, Universiti Tenaga Nasional

DOI:

https://doi.org/10.11113/jt.v68.3000

Keywords:

Optimization, plastic injection, DOE, SNR, bibliometrics

Abstract

Plastic injection molding is one of the most common methods of part manufacturing. Different optimization techniques are commonly used in this industry to satisfy for the multi-input multi-output (MIMO) characteristics of the injection process. The primary objective of this study is to provide a comparative Bibliometric analysis on injection molding process optimization during the previous decade based on the top seven methodologies found in the literature. Triple criteria of chronological trend, geographical dispersion and academic reputation are used for evaluating the overall performance of each method as well as each hybrid set. The survey will also include two complementary analyses for the Taguchi based methods. Firstly, a signal to noise ratio (SNR) analysis, followed by a secondary analysis of the average number of control and response factors as well as the orthogonal array levels used in the experimental design will be conducted. The results of the study reveal that Taguchi Method (TM), GA and RSM are the three most popular optimization techniques used in plastic injection molding worldwide. TM is also proved to be a better optimization tool when combined with other heuristic methods such as ANN and GA, especially in the field of product and mould design. For processing parameters, Taguchi still remains to be the core optimization technique. 

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Published

2014-05-15

How to Cite

Bariran, S. E. S., & Sahari, K. S. M. (2014). A Comparative Bibilometric Analysis of Taguchi-Centered Optimization in Plastic Injection Moulding. Jurnal Teknologi, 68(4). https://doi.org/10.11113/jt.v68.3000