Abstract
Gas Metal Arc Welding (GMAW) is one of the popular methods in joining metal in manufacturing industries. However the transient thermal stresses and non-uniform distribution of elastic strains is produced by the weld causes residual stresses and distortion, thus affecting the fatigue performance of the welded structure. The used of Robotic Welding (RW) allows this welding process parameters to be controlled significantly to improve the welding quality. First, Multi-Objective Taguchi Method (MTM) were used to analyse optimum parameters value which started application of common Taguchi methods (L8) Orthogonal Array (OA) and Total Normalized Quality Loss (TNQL) followed by ANOVA under simultaneous consideration response factors. The value was furthermore analysed by applying Multi-Signal to Noise Ratio (MSNR). The two (2) optimize welding parameter ranges are selected to be used for fatigue life assessment on the 9 mm plate which is labelled as set A and B. Tensile test was carried out on the specimen prior to fatigue testing to know the value of yield strength and UTS of the specimens. The fatigue test was carried out on three (3) type of specimen with one sample without any welding as controlled specimen. It can be concluded that welding parameters of set A is more superior for fatigue performance of this 9 mm low carbon steel plate.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Abidin, Azrriq Zainul UNSPECIFIED Wan Abdul Rahaman, Wan Emri UNSPECIFIED HP Manurung, Yupiter UNSPECIFIED Abu Bakar, Muhammad Raimiey UNSPECIFIED |
Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures > Metal manufactures. Metalworking |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Mechanical Engineering |
Journal or Publication Title: | Journal of Mechanical Engineering (JMechE) |
UiTM Journal Collections: | UiTM Journal > Journal of Mechanical Engineering (JMechE) |
ISSN: | 18235514 |
Volume: | SI 4 |
Number: | 1 |
Page Range: | pp. 143-153 |
Keywords: | Fatigue Life, Optimization, GMAW |
Date: | 2017 |
URI: | https://ir.uitm.edu.my/id/eprint/39254 |