| Issue |
MATEC Web Conf.
Volume 225, 2018
UTP-UMP-VIT Symposium on Energy Systems 2018 (SES 2018)
|
|
|---|---|---|
| Article Number | 06004 | |
| Number of page(s) | 6 | |
| Section | Economic, environmental, social, policy and utilization aspects of energy | |
| DOI | https://doi.org/10.1051/matecconf/201822506004 | |
| Published online | 05 November 2018 | |
Metal Injection Molding Process Parameters as A Function of Filling Performance of 3D Printed Polymer Mold
1
Center for Automotive Research and Electric Mobility, Department of Mechanical Engineering, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Malaysia
2
Department of Chemical Engineering, NFC Institute of Engineering and Fertilizer Research, 38000 Faisalabad, Pakistan
3
Interdisciplinary Centre for Advanced Material Simulations, Ruhr-Universität Bochum, 44801 Bochum, Germany
* Corresponding author: khurram.altaf@utp.edu.my
Metal injection molding (MIM) is a swift manufacturing process, which can produce complex and intricate parts with good repeatability and accuracy. However, to quickly address low-volume demands of customized MIM parts, manufacturing of mold could be a potential challenge. Typically, machined metal molds are used for MIM, but they are expensive and need more lead time. The machined metal mold becomes useless once the design is changed or requirement of MIM parts is met. Therefore, for MIM production of a low volume of highly customized parts, machined metal mold could be substituted by 3D printed polymer molds. However, knowledge of filling behavior of MIM feedstock in polymer mold is a grey area, which demands study to investigate the effects of injection parameters on mold filling. The present study investigates the effects of machine injection parameters on feedstock filling behavior in 3D printed polymer molds. An attempt has been made to determine the trend of feedstock filling in the polymer mold as a function of injection parameters. Further, the design of experiment (DOE) has been used to estimate the weight of injection parameters.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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