CAM即服务具有动态轨迹生成能力,可用于STEP-NC数控加工的工艺优化

IF 12.2 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL
Kaiyao Zhang, Wenlei Xiao, Xiangming Fan, Gang Zhao
{"title":"CAM即服务具有动态轨迹生成能力,可用于STEP-NC数控加工的工艺优化","authors":"Kaiyao Zhang,&nbsp;Wenlei Xiao,&nbsp;Xiangming Fan,&nbsp;Gang Zhao","doi":"10.1016/j.jmsy.2025.03.004","DOIUrl":null,"url":null,"abstract":"<div><div>The next generation of STEP-NC technology needs to achieve more intelligent process optimization. Currently, the calculation method of toolpath length in process optimization algorithms hinders the flexibility and adaptability of algorithm applications. Process optimization needs to generate toolpath based on dynamic process parameter combinations automatically. To address this issue, this paper deploys CAM on the cloud based on the STEP-NC edge-cloud collaboration system, enabling the automatic generation of toolpath through interaction with the process parameter optimization process. Building on this, a non-dominated sorting genetic algorithm III with CAM as a service (NSGAIII-CaaS) for process optimization is proposed. Additionally, a process optimization method for machining feature elements is introduced. Finally, the proposed method is applied to optimize process parameters for three features of a typical part from COMAC, targeting machining cost and machining time. The feasibility of the proposed method’s application in manufacturing enterprises is verified. Using the optimized process parameters for machining features, the cost is reduced by over 70%, efficiency is improved by 70%, and redundant toolpath in machining features are optimized.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 294-308"},"PeriodicalIF":12.2000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CAM as a Service with dynamic toolpath generation ability for process optimization in STEP-NC compliant CNC machining\",\"authors\":\"Kaiyao Zhang,&nbsp;Wenlei Xiao,&nbsp;Xiangming Fan,&nbsp;Gang Zhao\",\"doi\":\"10.1016/j.jmsy.2025.03.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The next generation of STEP-NC technology needs to achieve more intelligent process optimization. Currently, the calculation method of toolpath length in process optimization algorithms hinders the flexibility and adaptability of algorithm applications. Process optimization needs to generate toolpath based on dynamic process parameter combinations automatically. To address this issue, this paper deploys CAM on the cloud based on the STEP-NC edge-cloud collaboration system, enabling the automatic generation of toolpath through interaction with the process parameter optimization process. Building on this, a non-dominated sorting genetic algorithm III with CAM as a service (NSGAIII-CaaS) for process optimization is proposed. Additionally, a process optimization method for machining feature elements is introduced. Finally, the proposed method is applied to optimize process parameters for three features of a typical part from COMAC, targeting machining cost and machining time. The feasibility of the proposed method’s application in manufacturing enterprises is verified. Using the optimized process parameters for machining features, the cost is reduced by over 70%, efficiency is improved by 70%, and redundant toolpath in machining features are optimized.</div></div>\",\"PeriodicalId\":16227,\"journal\":{\"name\":\"Journal of Manufacturing Systems\",\"volume\":\"80 \",\"pages\":\"Pages 294-308\"},\"PeriodicalIF\":12.2000,\"publicationDate\":\"2025-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Manufacturing Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0278612525000664\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Manufacturing Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0278612525000664","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

摘要

下一代STEP-NC技术需要实现更加智能化的工艺优化。目前,工艺优化算法中刀具轨迹长度的计算方法阻碍了算法应用的灵活性和适应性。工艺优化需要基于动态工艺参数组合自动生成刀具路径。针对这一问题,本文基于STEP-NC边缘云协同系统在云端部署CAM,通过与工艺参数优化过程的交互,实现刀具轨迹的自动生成。在此基础上,提出了一种以CAM为服务的非支配排序遗传算法(NSGAIII-CaaS)。此外,还介绍了一种加工特征元件的工艺优化方法。最后,以加工成本和加工时间为目标,对中国商飞某典型零件的三个特征进行了工艺参数优化。验证了该方法在制造企业应用的可行性。利用优化后的加工特征工艺参数,成本降低70%以上,效率提高70%以上,并对加工特征中的冗余刀具轨迹进行了优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CAM as a Service with dynamic toolpath generation ability for process optimization in STEP-NC compliant CNC machining
The next generation of STEP-NC technology needs to achieve more intelligent process optimization. Currently, the calculation method of toolpath length in process optimization algorithms hinders the flexibility and adaptability of algorithm applications. Process optimization needs to generate toolpath based on dynamic process parameter combinations automatically. To address this issue, this paper deploys CAM on the cloud based on the STEP-NC edge-cloud collaboration system, enabling the automatic generation of toolpath through interaction with the process parameter optimization process. Building on this, a non-dominated sorting genetic algorithm III with CAM as a service (NSGAIII-CaaS) for process optimization is proposed. Additionally, a process optimization method for machining feature elements is introduced. Finally, the proposed method is applied to optimize process parameters for three features of a typical part from COMAC, targeting machining cost and machining time. The feasibility of the proposed method’s application in manufacturing enterprises is verified. Using the optimized process parameters for machining features, the cost is reduced by over 70%, efficiency is improved by 70%, and redundant toolpath in machining features are optimized.
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
Journal of Manufacturing Systems
Journal of Manufacturing Systems 工程技术-工程:工业
CiteScore
23.30
自引率
13.20%
发文量
216
审稿时长
25 days
期刊介绍: The Journal of Manufacturing Systems is dedicated to showcasing cutting-edge fundamental and applied research in manufacturing at the systems level. Encompassing products, equipment, people, information, control, and support functions, manufacturing systems play a pivotal role in the economical and competitive development, production, delivery, and total lifecycle of products, meeting market and societal needs. With a commitment to publishing archival scholarly literature, the journal strives to advance the state of the art in manufacturing systems and foster innovation in crafting efficient, robust, and sustainable manufacturing systems. The focus extends from equipment-level considerations to the broader scope of the extended enterprise. The Journal welcomes research addressing challenges across various scales, including nano, micro, and macro-scale manufacturing, and spanning diverse sectors such as aerospace, automotive, energy, and medical device manufacturing.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信