What is it about?
This research is an example of manufacturing analytics. It stems from a research project that focus on creating a fault detection system for metal cutting processes using process models and data analytics. As part of this research project, in this paper we introduced a novel method for detecting tool-related faults in milling processes using process simulation-based machine learning algorithms such as KNN and Random Forest classifiers.
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Why is it important?
We used data to determine the tool-related faults. This is among the first examples where data analytics and physical simulations are used for such a purpose.
Perspectives
I consider manufacturing analytics as a fertile field where both Data Analytics and Decision Making can contribute much. More examples with practical relevance is required in future
Prof. Kemal Kilic
Sabanci Universitesi
Read the Original
This page is a summary of: Smart Tool-Related Faults Monitoring System Using Process Simulation-Based Machine Learning Algorithms, Journal of Machine Engineering, October 2023, Wroclaw Board of Scientific Technical Societies Federation NOT,
DOI: 10.36897/jme/174018.
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