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

N. Dharani, Nandeesha H L
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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.
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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。
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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
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