TY  - CONF
VL  - 2934
A1  - Bharathy, N.K.A.M.
A1  - Mehat, N.M.
A1  - Kamaruddin, S.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188300113&doi=10.1063%2f5.0180610&partnerID=40&md5=3cd9c6708e9598c03afe75f1a351a1bb
PB  - American Institute of Physics
SN  - 0094243X
Y1  - 2024///
TI  - Multi-factors optimization of injection moulded plastic bearing via Taguchi method
ID  - scholars19810
N1  - cited By 0; Conference of 2nd International Conference on Science, Engineering and Technology, ICSET 2022 ; Conference Date: 6 July 2022 Through 7 July 2022; Conference Code:197941
N2  - During injection moulding process, there are numerous variables that have to be considered such as material selection, part and mould design as well as processing parameters. All the variables interact with each other to determine the quality of the plastic part. Inappropriate combination of material selection, part and mould design as well as processing parameters can cause numerous production problems, degradation in final mechanical properties or defects on the aesthetic appearance of the moulded part. Therefore, it is of utmost importance to effectively control all the influential factors to improve the quality characteristics of the final moulded part. In this study, Taguchi optimization method was proposed to be integrated in simulation and optimize all the factors including material selection, part and mould design as well as processing parameters and determine the significance of each factor on the quality of the moulded part. In this research, volumetric shrinkage, shear stress at wall and deflection were selected as quality characteristics to study the effect of material selection, part design and injection moulding processing parameters on the bearing outer cage. © 2024 Author(s).
AV  - none
ER  -