Multi objective optimization of weld parameters of boiler steel using fuzzy based desirability function

被引:0
|
作者
Satheesh, M. [1 ]
Edwin Raja Dhas, J. [2 ]
机构
[1] Dep. of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil nadu, India
[2] Dep. of Automobile Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil nadu, India
关键词
Multiobjective optimization - Boilers - Fuzzy logic - Construction industry - Submerged arc welding - Welds - Orthogonal functions;
D O I
10.25103/jestr.071.05
中图分类号
学科分类号
摘要
The high pressure differential across the wall of pressure vessels is potentially dangerous and has caused many fatal accidents in the history of their development and operation. For this reason the structural integrity of weldments is critical to the performance of pressure vessels. In recent years much research has been conducted to the study of variations in welding parameters and consumables on the mechanical properties of pressure vessel steel weldments to optimize weld integrity and ensure pressure vessels are safe. The quality of weld is a very important working aspect for the manufacturing and construction industries. Because of high quality and reliability, Submerged Arc Welding (SAW) is one of the chief metal joining processes employed in industry. This paper addresses the application of desirability function approach combined with fuzzy logic analysis to optimize the multiple quality characteristics (bead reinforcement, bead width, bead penetration and dilution) of submerged arc welding process parameters of SA 516 Grade 70 steels(boiler steel). Experiments were conducted using Taguchi's L27 orthogonal array with varying the weld parameters of welding current, arc voltage, welding speed and electrode stickout. By analyzing the response table and response graph of the fuzzy reasoning grade, optimal parameters were obtained. Solutions from this method can be useful for pressure vessel manufacturers and operators to search an optimal solution of welding condition. © 2014 Kavala Institute of Technology.
引用
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页码:29 / 36
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