手套生产智能停机监控系统研究

Abd Halim Embong, Fatin Diyana Yahya, Muhammad Mahbubur Rashid
{"title":"手套生产智能停机监控系统研究","authors":"Abd Halim Embong, Fatin Diyana Yahya, Muhammad Mahbubur Rashid","doi":"10.26776/ijemm.08.04.2023.04","DOIUrl":null,"url":null,"abstract":"The manufacturing industry is pushing forward with the smart machineries, linked networks, and a smart environment to enhance Big Data’s operations – gaining intelligence and actionable real-time insights for higher efficient and smart production. However, in many parts of the manufacturing industry, manual monitoring system is still the usual practice, especially the long-established plants that consist of legacy machines. The monitoring processes of the lines in Top Glove F31 such as recording the lines’ downtime duration, checking the source of the stoppage, transferring the data into spreadsheet, and analyzing the downtime of the lines are all being carried out by human operators. There is a high tendency for the workers to overlook the maintenance of the system because of this work practice, and it will contribute to higher unplanned downtime of the lines. Thus, this project proposes to design an automatic downtime monitoring system that consists of sensors, PLC’s programming, and IoT technologies that can decrease the dependency on workers and not prone to human mistakes to reduce the unplanned downtime of the lines and increase the efficiency of the system.","PeriodicalId":474637,"journal":{"name":"International Journal of Engineering Materials and Manufacture","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on Smart Downtime Monitoring System in Glove Production\",\"authors\":\"Abd Halim Embong, Fatin Diyana Yahya, Muhammad Mahbubur Rashid\",\"doi\":\"10.26776/ijemm.08.04.2023.04\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The manufacturing industry is pushing forward with the smart machineries, linked networks, and a smart environment to enhance Big Data’s operations – gaining intelligence and actionable real-time insights for higher efficient and smart production. However, in many parts of the manufacturing industry, manual monitoring system is still the usual practice, especially the long-established plants that consist of legacy machines. The monitoring processes of the lines in Top Glove F31 such as recording the lines’ downtime duration, checking the source of the stoppage, transferring the data into spreadsheet, and analyzing the downtime of the lines are all being carried out by human operators. There is a high tendency for the workers to overlook the maintenance of the system because of this work practice, and it will contribute to higher unplanned downtime of the lines. Thus, this project proposes to design an automatic downtime monitoring system that consists of sensors, PLC’s programming, and IoT technologies that can decrease the dependency on workers and not prone to human mistakes to reduce the unplanned downtime of the lines and increase the efficiency of the system.\",\"PeriodicalId\":474637,\"journal\":{\"name\":\"International Journal of Engineering Materials and Manufacture\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Engineering Materials and Manufacture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26776/ijemm.08.04.2023.04\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering Materials and Manufacture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26776/ijemm.08.04.2023.04","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

制造业正在推动智能机械、互联网络和智能环境的发展,以增强大数据的运营——获得智能和可操作的实时洞察,以实现更高效、更智能的生产。然而,在制造业的许多部分,人工监控系统仍然是通常的做法,特别是由遗留机器组成的历史悠久的工厂。Top Glove F31生产线的监控过程,如记录生产线停机时间、检查停机原因、将数据转换为电子表格、分析生产线停机时间等,都是由人工操作人员完成的。由于这种工作实践,工人很容易忽视系统的维护,这将导致生产线的计划外停机时间增加。因此,本项目建议设计一个由传感器、PLC编程和物联网技术组成的自动停机监控系统,可以减少对工人的依赖,不容易出现人为错误,以减少生产线的计划外停机时间,提高系统效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Smart Downtime Monitoring System in Glove Production
The manufacturing industry is pushing forward with the smart machineries, linked networks, and a smart environment to enhance Big Data’s operations – gaining intelligence and actionable real-time insights for higher efficient and smart production. However, in many parts of the manufacturing industry, manual monitoring system is still the usual practice, especially the long-established plants that consist of legacy machines. The monitoring processes of the lines in Top Glove F31 such as recording the lines’ downtime duration, checking the source of the stoppage, transferring the data into spreadsheet, and analyzing the downtime of the lines are all being carried out by human operators. There is a high tendency for the workers to overlook the maintenance of the system because of this work practice, and it will contribute to higher unplanned downtime of the lines. Thus, this project proposes to design an automatic downtime monitoring system that consists of sensors, PLC’s programming, and IoT technologies that can decrease the dependency on workers and not prone to human mistakes to reduce the unplanned downtime of the lines and increase the efficiency of the system.
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:604180095
Book学术官方微信