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IJEMS

Vol. 8 No. 3 (2023)
Mechanical and Vehicle Engineering

Manufacturing Process Optimization and Tool Condition Monitoring in Mechanical Engineering

Published:
2023-09-29
DOI Linkhttps://doi.org/10.21791/IJEMS.2023.026
Authors
Krisztián Deák,
József Menyhárt
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Keywords
Tecnomatix plant simulation tool, wear diagnosis machine learning
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Copyright (c) 2023 Krisztián Deák, József Menyhárt

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How To Cite
Selected Style: APA
Deák, K., & Menyhárt, J. (2023). Manufacturing Process Optimization and Tool Condition Monitoring in Mechanical Engineering. International Journal of Engineering and Management Sciences, 8(3), 72-89. https://doi.org/10.21791/IJEMS.2023.026
Received 2023-01-21
Accepted 2023-03-20
Published 2023-09-29
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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