评估金属加工机械的使用寿命:智能监控视角

Hsiao-Yu Wang, Ching-Hua Hung, Cheng-Hui Chen
{"title":"评估金属加工机械的使用寿命:智能监控视角","authors":"Hsiao-Yu Wang, Ching-Hua Hung, Cheng-Hui Chen","doi":"10.1007/s11036-024-02353-5","DOIUrl":null,"url":null,"abstract":"<p>This investigation addresses a range of critical challenges within the domain of mechanical engineering and anticipates their potential impacts. The study’s goals include developing methods for detecting tool breakage in integrated milling-turning machines, evaluating the service life of punching machine components, and determining the durability of molds in forging equipment, alongside other complex issues. The primary aim is to devise a specialized equipment health diagnostic system, designed for complex industrial environments. Industry consultation has revealed that effective monitoring strategies and threshold values must be tailored to the specific characteristics of each piece of equipment and their respective sectors. Despite the metal processing industry lagging roughly a decade behind the semiconductor sector in adopting intelligent monitoring systems, it encounters similar hurdles. These include shrinking labor demographics necessitating increased reliance on shift-based external labor, higher turnover rates impacting the retention of skilled workers for essential tasks such as tool replacements and machinery maintenance. Furthermore, there is a pressing need to maintain traceability for the usage history of molds and punching heads, especially to meet aerospace industry regulations. In response, the sector aims to accomplish two primary goals for its critical production machinery: firstly, to implement diagnostic tools for evaluating the wear and overall quality of tools and molds; secondly, to shift from time-based to condition-based maintenance protocols, adaptable to the frequent mold changes required for varied product fabrication.</p>","PeriodicalId":501103,"journal":{"name":"Mobile Networks and Applications","volume":"76 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating Service Life of Metal Processing Machinery: An Intelligent Monitoring Perspective\",\"authors\":\"Hsiao-Yu Wang, Ching-Hua Hung, Cheng-Hui Chen\",\"doi\":\"10.1007/s11036-024-02353-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This investigation addresses a range of critical challenges within the domain of mechanical engineering and anticipates their potential impacts. The study’s goals include developing methods for detecting tool breakage in integrated milling-turning machines, evaluating the service life of punching machine components, and determining the durability of molds in forging equipment, alongside other complex issues. The primary aim is to devise a specialized equipment health diagnostic system, designed for complex industrial environments. Industry consultation has revealed that effective monitoring strategies and threshold values must be tailored to the specific characteristics of each piece of equipment and their respective sectors. Despite the metal processing industry lagging roughly a decade behind the semiconductor sector in adopting intelligent monitoring systems, it encounters similar hurdles. These include shrinking labor demographics necessitating increased reliance on shift-based external labor, higher turnover rates impacting the retention of skilled workers for essential tasks such as tool replacements and machinery maintenance. Furthermore, there is a pressing need to maintain traceability for the usage history of molds and punching heads, especially to meet aerospace industry regulations. In response, the sector aims to accomplish two primary goals for its critical production machinery: firstly, to implement diagnostic tools for evaluating the wear and overall quality of tools and molds; secondly, to shift from time-based to condition-based maintenance protocols, adaptable to the frequent mold changes required for varied product fabrication.</p>\",\"PeriodicalId\":501103,\"journal\":{\"name\":\"Mobile Networks and Applications\",\"volume\":\"76 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mobile Networks and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s11036-024-02353-5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mobile Networks and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11036-024-02353-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

这项调查涉及机械工程领域的一系列关键挑战,并预测其潜在影响。研究的目标包括开发检测车铣复合机床刀具破损的方法、评估冲床部件的使用寿命、确定锻造设备模具的耐用性以及其他复杂问题。主要目的是设计一种专门的设备健康诊断系统,用于复杂的工业环境。行业咨询显示,有效的监测策略和阈值必须针对每台设备及其各自行业的具体特点。尽管金属加工行业在采用智能监控系统方面比半导体行业落后大约十年,但也遇到了类似的障碍。这些障碍包括:劳动力人口减少,需要更多地依赖轮班制的外部劳动力;人员流动率较高,影响了工具更换和机器维护等基本任务的熟练工人的留用。此外,还迫切需要对模具和冲压头的使用历史保持可追溯性,特别是要符合航空航天行业的规定。为此,该行业旨在实现其关键生产设备的两个主要目标:第一,采用诊断工具来评估工具和模具的磨损情况和整体质量;第二,从基于时间的维护协议转变为基于状态的维护协议,以适应各种产品制造所需的频繁模具更换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluating Service Life of Metal Processing Machinery: An Intelligent Monitoring Perspective

Evaluating Service Life of Metal Processing Machinery: An Intelligent Monitoring Perspective

This investigation addresses a range of critical challenges within the domain of mechanical engineering and anticipates their potential impacts. The study’s goals include developing methods for detecting tool breakage in integrated milling-turning machines, evaluating the service life of punching machine components, and determining the durability of molds in forging equipment, alongside other complex issues. The primary aim is to devise a specialized equipment health diagnostic system, designed for complex industrial environments. Industry consultation has revealed that effective monitoring strategies and threshold values must be tailored to the specific characteristics of each piece of equipment and their respective sectors. Despite the metal processing industry lagging roughly a decade behind the semiconductor sector in adopting intelligent monitoring systems, it encounters similar hurdles. These include shrinking labor demographics necessitating increased reliance on shift-based external labor, higher turnover rates impacting the retention of skilled workers for essential tasks such as tool replacements and machinery maintenance. Furthermore, there is a pressing need to maintain traceability for the usage history of molds and punching heads, especially to meet aerospace industry regulations. In response, the sector aims to accomplish two primary goals for its critical production machinery: firstly, to implement diagnostic tools for evaluating the wear and overall quality of tools and molds; secondly, to shift from time-based to condition-based maintenance protocols, adaptable to the frequent mold changes required for varied product fabrication.

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
×
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