磨料水射流加工AA5083不同厚度的试验研究

Q3 Engineering

International Journal of Abrasive Technology Pub Date : 2018-08-22 DOI:10.1504/IJAT.2018.10015291

G. Selvakumar, S. Prakash, N. Lenin

{"title":"磨料水射流加工AA5083不同厚度的试验研究","authors":"G. Selvakumar, S. Prakash, N. Lenin","doi":"10.1504/IJAT.2018.10015291","DOIUrl":null,"url":null,"abstract":"The objective of this study is to present the optimal machining parameters for abrasive water jet machining (AWJM) of Aluminium alloy 5083 (AA5083) by employing artificial neural networks (ANN) modelling for various material thicknesses. Al 5083 alloy finds vast applications in ship building, rail cars, and vehicle bodies and exclusively for cryogenic applications. The experimental work was carried out by using Taguchi L18 orthogonal array to study the influence of the process parameters such as jet diameter, stand-off distance and abrasive flow rate for various ranges of thicknesses over the process yields namely material removal rate (mrr), surface roughness and taper error. Technological table for optimal machining of AA5083 alloy in AWJM was reported for ready to use in industry.","PeriodicalId":39039,"journal":{"name":"International Journal of Abrasive Technology","volume":"8 1","pages":"218"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Experimental study on abrasive water jet machining of AA5083 in a range of thicknesses\",\"authors\":\"G. Selvakumar, S. Prakash, N. Lenin\",\"doi\":\"10.1504/IJAT.2018.10015291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this study is to present the optimal machining parameters for abrasive water jet machining (AWJM) of Aluminium alloy 5083 (AA5083) by employing artificial neural networks (ANN) modelling for various material thicknesses. Al 5083 alloy finds vast applications in ship building, rail cars, and vehicle bodies and exclusively for cryogenic applications. The experimental work was carried out by using Taguchi L18 orthogonal array to study the influence of the process parameters such as jet diameter, stand-off distance and abrasive flow rate for various ranges of thicknesses over the process yields namely material removal rate (mrr), surface roughness and taper error. Technological table for optimal machining of AA5083 alloy in AWJM was reported for ready to use in industry.\",\"PeriodicalId\":39039,\"journal\":{\"name\":\"International Journal of Abrasive Technology\",\"volume\":\"8 1\",\"pages\":\"218\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Abrasive Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJAT.2018.10015291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Abrasive Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJAT.2018.10015291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}

引用次数: 14

摘要

本研究的目的是利用人工神经网络(ANN)对不同材料厚度进行建模，给出磨料水射流加工5083铝合金(AA5083)的最佳加工参数。al5083合金广泛应用于船舶制造，轨道车辆和车辆车身，并专门用于低温应用。实验采用田口L18正交阵列，研究了不同厚度范围内射流直径、间隙距离和磨料流量等工艺参数对材料去除率、表面粗糙度和锥度误差等工艺产量的影响。报道了在AWJM中优化加工AA5083合金的工艺表，准备在工业上应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Experimental study on abrasive water jet machining of AA5083 in a range of thicknesses

The objective of this study is to present the optimal machining parameters for abrasive water jet machining (AWJM) of Aluminium alloy 5083 (AA5083) by employing artificial neural networks (ANN) modelling for various material thicknesses. Al 5083 alloy finds vast applications in ship building, rail cars, and vehicle bodies and exclusively for cryogenic applications. The experimental work was carried out by using Taguchi L18 orthogonal array to study the influence of the process parameters such as jet diameter, stand-off distance and abrasive flow rate for various ranges of thicknesses over the process yields namely material removal rate (mrr), surface roughness and taper error. Technological table for optimal machining of AA5083 alloy in AWJM was reported for ready to use in industry.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Abrasive Technology Engineering-Industrial and Manufacturing Engineering

CiteScore

0.90

自引率

0.00%

发文量