IJERT-Parametric Optimisation of Gas Metal arc Welding Process with the Help of Taguchi Method on Tensile Strength – A Review (original) (raw)

Utility Fuzzy Taguchi Optimization Multiple Quality Factors of Submerged Arc Welding.pdf

Submerged Arc Welding (SAW) process is an essential metal joining processes in industry. The applications of SAW are as pressure vessels, heat exchanger, line piping, steel structural, nuclear industries and petroleum industries due to its high quality welds. The present work aims are to investigate the optimization of SAW parameters of selected material SA516 grade 70 steel of 10 mm thickness, in order to obtain desired mechanical properties of weld joint. Selection of process parameters has great influence on the weld quality, which is one of a problem faces manufacturer. SAW is multi input and multi output process, the multiple response optimization theory which is utility-based fuzzy logic coupled with Taguchi L9 orthogonal array was implemented. Three SAW process parameters were investigated such as welding current, arc voltage and welding speed with three varying levels. For welding current (300, 350 and 400 Amps.), three levels of arc voltage are (32, 36 and 40 V) and three level of welding speed (26, 28 and 30 cm/min) were used to weld sample plates measuring 500×500×10 mm. The weld quality and properties were evaluated using ultimate tensile strength, ultimate bending force, HB macrohardness and Charpy impact which are selected as performance characteristics, weld geometry measurements and non-destructive test such as visual inspection, penetrated liquid and X-ray radiography. Method of utility-based fuzzy logic converts the complex multiple objectives into a single utility which is Multi Performance Characteristics Index (MPCI). Fuzzy logic was used to reduce the degree of uncertainty in the output. MPCI values of responses measured using fuzzy inference system type Mamdani. MPCI is optimized using the S/N ratio analysis. The experimental results were analyzed by using Minitab®17 program and MATLAB software. The results show the optimal SAW parameters setting are welding current= 400 Amps, arc voltage= 40 V and welding speed= 30 cm/min. Significant contributions of parameters are estimated using analysis of variance (ANOVA). P values for welding current, arc voltage and welding speed are below interval significance (α)= 0.05 which meaning that all process parameters have significant effects. The contribution of welding current had major influence with percentage (37.03%), welding speed had (32.9%) effects and arc voltage had least (30.07%) contribution to influence on response parameters.