Journal of Applied Science and Engineering

Published by Tamkang University Press


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Chiwapon Nitnara, Kumpon TragangoonThis email address is being protected from spambots. You need JavaScript enabled to view it., and Sakchai Muangpasee

Department of Mechanical Engineering Technology, College of Industrial Technology, King Mongkut’s University of Technology North Bangkok 10800, Thailand


Received: October 11, 2023
Accepted: November 29, 2023
Publication Date: December 29, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Plastic injection molding is a widely used manufacturing technique for producing various plastic components and consuming more energy. However, energy efficiency has become critical due to the increasing energy costs and related environmental impact. This study aimed to optimize the injection molding process parameters to reduce energy consumption while maintaining product quality using a Design of Experiment (DOE) approach combined with the Taguchi method and Computer-Aided Engineering (CAE). The parameters considered included an injection rate ranging from 80 to 106 cm3/sec, injection pressures of 72 – 101.5 MPa, and packing pressure from 72 – 101.5 MPa. From these optimized parameters, actual injection molding experiments were conducted and compared with conventional plastic injection processes. The research findings revealed that using optimized parameters in the new process reduced energy consumption by 6.39%, product shrinkage by 38.98%, and the density remained within an acceptable range of 1.053 g/cc for polystyrene (PS). Furthermore, these results offered manufacturers actionable insights into selecting the most effective process parameters and leaded the way for more sustainable and resource-efficient plastic injection molding practices.

Keywords: Taguchi Method, Design of Experiment, Computer-Aided Engineering, Energy Efficiency, Molding Parameters, Residual Stress

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