基于计算机辅助制造系统实验设计的“按区域粗加工”的刀具路径策略决策

G. Vosniakos, Asimina Gkortza, N. Kontolatis
{"title":"基于计算机辅助制造系统实验设计的“按区域粗加工”的刀具路径策略决策","authors":"G. Vosniakos, Asimina Gkortza, N. Kontolatis","doi":"10.1504/IJMR.2016.076985","DOIUrl":null,"url":null,"abstract":"This work streamlines assignment of roughing strategies for complex parts from those that are available on a computer-aided manufacturing (CAM) system. A Pelton hydro-turbine bucket is used as an example, divided into independent regions. For each region the applicable strategies, toolpath types, as well as their individual parameters are examined at a small enough number of discrete levels to ensure practical feasibility. The responses, i.e. machining time and rest material, are combined into a single weighting function. The absolute minimum number of possible scenarios is guaranteed by Taguchi design and the optimum factor levels are determined. Analysis of variance reveals the significance of each factor but also possible omissions of factors and/or interactions that may occur. The approach saves time, is open to rectification by simply adding the missing experiments and is equally applicable to any mechanical component to be machined. [Received 30 September 2015; Revised 17 February 2016; Accepted 23 February 2016]","PeriodicalId":154059,"journal":{"name":"Int. J. Manuf. Res.","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Toolpath strategy decisions in 'rough machining-by-region' using design of experiments on computer-aided manufacturing systems\",\"authors\":\"G. Vosniakos, Asimina Gkortza, N. Kontolatis\",\"doi\":\"10.1504/IJMR.2016.076985\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work streamlines assignment of roughing strategies for complex parts from those that are available on a computer-aided manufacturing (CAM) system. A Pelton hydro-turbine bucket is used as an example, divided into independent regions. For each region the applicable strategies, toolpath types, as well as their individual parameters are examined at a small enough number of discrete levels to ensure practical feasibility. The responses, i.e. machining time and rest material, are combined into a single weighting function. The absolute minimum number of possible scenarios is guaranteed by Taguchi design and the optimum factor levels are determined. Analysis of variance reveals the significance of each factor but also possible omissions of factors and/or interactions that may occur. The approach saves time, is open to rectification by simply adding the missing experiments and is equally applicable to any mechanical component to be machined. [Received 30 September 2015; Revised 17 February 2016; Accepted 23 February 2016]\",\"PeriodicalId\":154059,\"journal\":{\"name\":\"Int. J. Manuf. Res.\",\"volume\":\"121 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Manuf. Res.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJMR.2016.076985\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Manuf. Res.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJMR.2016.076985","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

这项工作简化了计算机辅助制造(CAM)系统中复杂零件的粗加工策略分配。以Pelton水轮机铲斗为例,将其划分为独立的区域。对于每个区域,适用的策略,工具路径类型,以及它们各自的参数都在足够小的离散级别上进行检查,以确保实际的可行性。响应,即加工时间和休息材料,被组合成一个单一的加权函数。田口设计保证了可能情况的绝对最小数量,并确定了最佳因子水平。方差分析揭示了每个因素的重要性,但也可能遗漏因素和/或可能发生的相互作用。该方法节省了时间,可以通过简单地添加缺失的实验来进行修正,并且同样适用于任何要加工的机械部件。[2015年9月30日收到;2016年2月17日修订;接受2016年2月23日]
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Toolpath strategy decisions in 'rough machining-by-region' using design of experiments on computer-aided manufacturing systems
This work streamlines assignment of roughing strategies for complex parts from those that are available on a computer-aided manufacturing (CAM) system. A Pelton hydro-turbine bucket is used as an example, divided into independent regions. For each region the applicable strategies, toolpath types, as well as their individual parameters are examined at a small enough number of discrete levels to ensure practical feasibility. The responses, i.e. machining time and rest material, are combined into a single weighting function. The absolute minimum number of possible scenarios is guaranteed by Taguchi design and the optimum factor levels are determined. Analysis of variance reveals the significance of each factor but also possible omissions of factors and/or interactions that may occur. The approach saves time, is open to rectification by simply adding the missing experiments and is equally applicable to any mechanical component to be machined. [Received 30 September 2015; Revised 17 February 2016; Accepted 23 February 2016]
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
自引率
0.00%
发文量
0
期刊最新文献
Computer simulation and optimisation of material handling systems FEM assessment of the effects of machining parameters in vibration assisted nano impact machining of silicon by loose abrasives Prediction of three-dimensional coordinate measurement of space points based on BP neural network An integrated approach for multi-period manufacturing planning of job-shops Supplier evaluation and selection based on quality matchable degree
×
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