Modelling and simulation of hot direct extrusion process for optimal product characteristics: Single and multi-response optimization approach

F. Elplacy, M. Samuel, R. Mostafa
{"title":"Modelling and simulation of hot direct extrusion process for optimal product characteristics: Single and multi-response optimization approach","authors":"F. Elplacy, M. Samuel, R. Mostafa","doi":"10.14743/apem2022.1.419","DOIUrl":null,"url":null,"abstract":"The study of eccentricity minimization in cylindrical products helps to reduce the mechanical vibrations and wear of related mechanical parts such as bearings, columns and gears which positively affects in maintenance costs savings and increasing production quality reliability. The main purpose of this paper is to investigate the effect of the eccentricity between the billet material and the die parts on the quality of the final product in the direct extrusion process. The input parameters to produce a cylindrical product shape are optimized in MINITAB based on Taguchi method and ANOVA. The selected material of the billet is the aluminium alloy AA2024, and the die material is Steel H13. The inputs parameters are the temperature, the die angle, the ram speed, and the presumed eccentricity. The finite element model of the process is simulated in DFORM-3D for providing the extrusion information such as the pressure, the effective stress and strain, the final product eccentricity, and the roundness error. The study is carried out on two cases of the presumed eccentricity in addition to a case of zero eccentricity. The single and multi-response optimizations are executed to obtain the optimum parameters for the minimum product eccentricity and roundness error.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Production Engineering & Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14743/apem2022.1.419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The study of eccentricity minimization in cylindrical products helps to reduce the mechanical vibrations and wear of related mechanical parts such as bearings, columns and gears which positively affects in maintenance costs savings and increasing production quality reliability. The main purpose of this paper is to investigate the effect of the eccentricity between the billet material and the die parts on the quality of the final product in the direct extrusion process. The input parameters to produce a cylindrical product shape are optimized in MINITAB based on Taguchi method and ANOVA. The selected material of the billet is the aluminium alloy AA2024, and the die material is Steel H13. The inputs parameters are the temperature, the die angle, the ram speed, and the presumed eccentricity. The finite element model of the process is simulated in DFORM-3D for providing the extrusion information such as the pressure, the effective stress and strain, the final product eccentricity, and the roundness error. The study is carried out on two cases of the presumed eccentricity in addition to a case of zero eccentricity. The single and multi-response optimizations are executed to obtain the optimum parameters for the minimum product eccentricity and roundness error.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
热直接挤压过程优化产品特性的建模与仿真:单响应和多响应优化方法
圆柱产品偏心最小化的研究有助于减少轴承、圆柱和齿轮等相关机械部件的机械振动和磨损,从而对节省维护成本和提高生产质量可靠性产生积极影响。本文的主要目的是研究直接挤压过程中坯料与模具零件之间的偏心对最终产品质量的影响。基于田口法和方差分析,在MINITAB中优化了圆柱形产品的输入参数。坯料选用的材料为铝合金AA2024,模具选用的材料为钢H13。输入参数是温度、模具角度、滑枕速度和假定偏心。在DFORM-3D中对该工艺的有限元模型进行了仿真,提供了挤压压力、有效应力应变、最终产品偏心和圆度误差等信息。研究了两种假定偏心和一种零偏心的情况。通过单响应优化和多响应优化,获得了产品偏心和圆度误差最小的最优参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Optimizing smart manufacturing systems using digital twin IoT-based Deep Learning Neural Network (DLNN) algorithm for voltage stability control and monitoring of solar power generation Reduction of surface defects by optimization of casting speed using genetic programming: An industrial case study Incentive modeling analysis in engineering applications and projects with stochastic duration time Comparing Fault Tree Analysis methods combined with Generalized Grey Relation Analysis: A new approach and case study in the automotive industry
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1