Optimization of single-track deposits in wire arc-based direct energy deposition of ER110S-G steel using MONS-MFO and TOPSIS algorithms

IF 1.9 3区 工程技术 Q3 ENGINEERING, MANUFACTURING
Van Thao Le, Thuy Duong Nguyen, Tien-Dat Hoang, Van-Canh Nguyen
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引用次数: 0

Abstract

Wire and arc-based direct energy deposition (wire and arc DED) is a promising metallic additively manufacturing (MAM) technology to fabricate large-size metallic components. Among high-strength-low-alloy steels used in wire and arc DED processes, ER110S-G is a commonly used material. However, previous studies have often relied on process parameters recommended by suppliers for conventional welding methods. This study aims to predict the optimum processing parameters for the manufacture of ER110S-G steel by a wire and arc DED process based on experiment and multi-attribute optimization algorithms. The experiment was designed using the full factorial method with the input variables ( U– voltage, I– current, and v– traveling speed) while considering three attributes of single tracks ( STW– single track width, STH– single track height, and LMP– length of melting pool). To find the optimal processing variables, MONS-MFO (Multi-Objective Non-Sorted Moth Flame) was utilized. The outcomes reveal that the developed predictive models of attributes feature a high accurate level ( R2 = 98.11%, 98.38%, and 98.07% for STW, STH, and LMP, respectively). The optimal parameters obtained by MONS-MFO & TOPSIS were I = 159.4 A, v = 0.3 m/min, and U = 21.4 V allow fabricating single tracks with smooth and regular shape and a s-shaped thin-wall component with regular shape and height. Moreover, no spatters generated with the optimal parameters, demonstrating their suitability and efficiency for the printing process.
使用 MONS-MFO 和 TOPSIS 算法优化 ER110S-G 钢线弧直接能量沉积中的单轨沉积物
基于线弧的直接能量沉积(线弧直接能量沉积)是一种很有前途的金属添加制造(MAM)技术,可用于制造大型金属部件。在线材和电弧直接能量沉积工艺中使用的高强度低合金钢中,ER110S-G 是一种常用材料。然而,以往的研究通常依赖于供应商为传统焊接方法推荐的工艺参数。本研究旨在基于实验和多属性优化算法,预测采用焊丝和电弧 DED 工艺制造 ER110S-G 钢的最佳工艺参数。实验采用全因子法设计,输入变量为 U-电压、I-电流和 v-行进速度,同时考虑了单轨的三个属性(STW-单轨宽度、STH-单轨高度和 LMP-熔池长度)。为了找到最佳处理变量,使用了多目标非排序蛾焰(MONS-MFO)。结果表明,所开发的属性预测模型具有较高的准确度(STW、STH 和 LMP 的 R2 分别为 98.11%、98.38% 和 98.07%)。通过 MONS-MFO 和 TOPSIS 得出的最佳参数为 I = 159.4 A,v = 0.3 m/min,U = 21.4 V,可以制造出形状光滑规则的单轨和形状和高度规则的 s 型薄壁组件。此外,在最佳参数下不会产生飞溅物,这表明其适用于印刷工艺并具有很高的效率。
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来源期刊
CiteScore
5.10
自引率
30.80%
发文量
167
审稿时长
5.1 months
期刊介绍: Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed. Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing. Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.
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