Optimisation of GTAW Parameters for the Tensile Strength of AISI 304 Stainless Steel Welds Using the Taguchi Method

2012 ◽  
Vol 54 (3) ◽  
pp. 163-168 ◽  
Author(s):  
Rukiye Ertan
2020 ◽  
Vol 62 (9) ◽  
pp. 957-961
Author(s):  
Nursel Altan Özbek ◽  
Metin İbrahim Karadag ◽  
Onur Özbek

Abstract This paper presents the effect of cutting tool, cutting speed and feed rate on the flank wear and surface roughness of austenitic stainless steel (AISI 304) during wet turning. Turning tests were designed based on the Taguchi method (L18). An orthogonal array, the signal-to-noise ratio (S/N) and the ANOVA were used to investigate the machinability of AISI 304 stainless steel with PVD and CVD coated tungsten carbide inserts. As a result of ANOVA, it was found that the feed rate was the most effective parameter on both flank wear and surface roughness.


2011 ◽  
Vol 117-119 ◽  
pp. 402-408
Author(s):  
Shazarel Shamsudin ◽  
Phoon Chee Yoon

Product with low cost, lightweight and enhanced mechanical properties were the main reasons welding dissimilar materials thrived by most of the industries. The laser welding technique which has high-energy density beam was found suitable of carrying this task. This paper attempts to investigate welding of AISI 304 stainless steel to AISI 1008 steel through Nd:YAG pulse laser method. The main objective of this study was to find out the weldability of these materials and investigate the mechanical properties of the welded butt joints. Peak power, pulse duration and weld speed combinations were carefully selected with the aims of producing weld with a good tensile strength, minimum heat affected zone (HAZ) and acceptable welding profile. Response surface methodology (RSM) approach was adopted as statistical design technique for tensile strength optimization. Statistical based mathematical model was developed to describe effects of each process parameters on the weld tensile strength and for response prediction within the parameter ranges. The microstructure of the weld and heat affected zones were observed via optical microscope. The results indicate the developed model can predict the response within ±9% of error from the actual values.


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