Design and Development of an IoT Kit To Predict Cutting Tool Life and Generate Auto Inventory

Q4 Energy
N. Dharani, Nandeesha H L
{"title":"Design and Development of an IoT Kit To Predict Cutting Tool Life and Generate Auto Inventory","authors":"N. Dharani, Nandeesha H L","doi":"10.18311/jmmf/2022/32934","DOIUrl":null,"url":null,"abstract":"For the best tool life, machining precision, and maintenance, a cutting tool life prediction is crucial. As a result, an online smart diagnosis service must be created to establish an auto inventory and anticipate the cutting tool life based on temperature data. Due to the fast-cutting velocity and high work material strength, diffusion wear becomes predominant when the cutting temperature rises significantly. Based on sensorial data gathered at the factory level, knowledge-based algorithms conduct online-based inspections on utilized tool life including tool breakage occurrence. Because heat load influences tool wear rate, a thermistor is fitted to the cutting tool to alert the database server when the temperature rises. based on the data.","PeriodicalId":39575,"journal":{"name":"Journal of Mines, Metals and Fuels","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mines, Metals and Fuels","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18311/jmmf/2022/32934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0

Abstract

For the best tool life, machining precision, and maintenance, a cutting tool life prediction is crucial. As a result, an online smart diagnosis service must be created to establish an auto inventory and anticipate the cutting tool life based on temperature data. Due to the fast-cutting velocity and high work material strength, diffusion wear becomes predominant when the cutting temperature rises significantly. Based on sensorial data gathered at the factory level, knowledge-based algorithms conduct online-based inspections on utilized tool life including tool breakage occurrence. Because heat load influences tool wear rate, a thermistor is fitted to the cutting tool to alert the database server when the temperature rises. based on the data.
物联网套件的设计和开发,以预测刀具寿命并生成自动库存
为了获得最佳的刀具寿命、加工精度和维护,刀具寿命预测是至关重要的。因此,必须创建在线智能诊断服务,以建立自动库存,并根据温度数据预测刀具寿命。由于切削速度快,工作材料强度高,当切削温度显著升高时,扩散磨损占优势。基于在工厂层面收集的传感器数据,基于知识的算法对使用的刀具寿命进行在线检查,包括刀具破损情况。由于热负荷会影响刀具的磨损率,因此在刀具上安装了一个热敏电阻,以便在温度升高时提醒数据库服务器。根据数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Mines, Metals and Fuels
Journal of Mines, Metals and Fuels Energy-Fuel Technology
CiteScore
0.20
自引率
0.00%
发文量
101
×
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