Staff Members - Benha University
A Comparison between FSW, MIG and TIG Based on Total Cost Estimation for Aluminum Pipes
European Journal of Advances in Engineering and Technology • 2017
Publication Information
Authors
A.M.El-Kassas, Ibraheem Sabry,
Keywords
FSW, MIG, TIG, Aluminium pipe, cost analysis
Journal
European Journal of Advances in Engineering and Technology
Publisher
Not Available
Volume
4
Issue
3
Pages
Not Available
publication.type
Local
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
In this Work, a comprehensive practical study in total cost estimation of welded Aluminum 6061 pipes using three
different types of welds, Metal Inert Gas (MIG), Tungsten Inert Gas (TIG) and Friction Stir Welding (FSW) . The
cost component of joining Al 6061 aluminum pipe welding was each component cost (labor cost, Power cost, Ma-
chine cost, shield gas cost(MIG,TIG), filler metal cost(MIG,TIG) and Tool cost(FSW)) has been closely analyzed
and major cost components have been included in the cost model. We used these cost models to predict the cost of
Metal Inert Gas (MIG), Tungsten Inert Gas (TIG) and friction stir welded pipe joints. Initial results show that MIG
and TIG welding were less cost effective compared to FS welding, but it is possible that the cost of reduced friction
stirs welding with quantitative prediction.
different types of welds, Metal Inert Gas (MIG), Tungsten Inert Gas (TIG) and Friction Stir Welding (FSW) . The
cost component of joining Al 6061 aluminum pipe welding was each component cost (labor cost, Power cost, Ma-
chine cost, shield gas cost(MIG,TIG), filler metal cost(MIG,TIG) and Tool cost(FSW)) has been closely analyzed
and major cost components have been included in the cost model. We used these cost models to predict the cost of
Metal Inert Gas (MIG), Tungsten Inert Gas (TIG) and friction stir welded pipe joints. Initial results show that MIG
and TIG welding were less cost effective compared to FS welding, but it is possible that the cost of reduced friction
stirs welding with quantitative prediction.