Manufacturing Process Optimization and Tool Condition Monitoring in Mechanical Engineering

Krisztián Deák, József Menyhárt
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Abstract

The optimization of manufacturing and production processes with various computer software is essential these days. Solutions on the market allow us to optimize and improve our manufacturing and production processes; one of the most popular software is called Tecnomatrix, which is described in this paper. Tool condition monitoring is a vital part of the manufacturing process in the industry. It requires continuous measurement of the wear of the cutting tool edges to improve the surface quality of the work piece and maintain productivity. Multiple methods are available for the determination of the actual condition of the cutting tool. Vibration diagnostics and acoustic methods are included in this paper. These methods are simple, it requires only high sensitive sensors, microphones, and data acquisition unit to gather the vibration signal and make signal improvement. Extended Taylor equation is applied for tool edge wear ratio. Labview and Matlab software are applied for the measurement and the digital signal processing. Machine learning method with artificial neural network is for the detection and prediction of the edge wear to estimate the remaining useful lifetime (RUL) of the tool.
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机械工程中的制造工艺优化与刀具状态监测
如今,利用各种计算机软件对制造和生产过程进行优化是必不可少的。市场上的解决方案使我们能够优化和改进我们的制造和生产流程;其中最流行的软件是Tecnomatrix,本文对其进行了描述。刀具状态监测是工业制造过程的重要组成部分。它要求对刀具刃口的磨损进行连续测量,以提高工件的表面质量,保持生产率。有多种方法可用于确定刀具的实际状况。本文包括振动诊断和声学方法。这些方法简单,只需要高灵敏度的传感器、麦克风和数据采集单元即可采集振动信号并进行信号改进。刀具刃口磨损率采用扩展泰勒方程。采用Labview和Matlab软件进行测量和数字信号处理。基于人工神经网络的机器学习方法是对刀具边缘磨损进行检测和预测,以估计刀具的剩余使用寿命。
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来源期刊
CiteScore
3.80
自引率
6.20%
发文量
57
审稿时长
20 weeks
期刊介绍: IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.
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