{"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}
引用次数: 0
Abstract
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.