Vibration-based tool life monitoring for ceramics micro-cutting under various toolpath strategies

Authors

DOI:

https://doi.org/10.21014/acta_imeko.v10i3.1063

Abstract

The 21st century manufacturing technology is unimagined without the various CAM (Computer Aided Manufacturing) toolpath generation programs. The aims of developing the toolpath strategies which are offered by the cutting control software is to ensure the longest possible tool lifetime and high efficiency of the cutting method. In this paper, the goal is to compare the efficiency of the 3 types of tool path strategies in the very special field of micro-milling of ceramic materials. The dimensional distortion of the manufactured geometries served to draw the Taylor curve for describing the wearing progress of the cutting tool helping to determine the worn-in, normal and wear out stages. These isolations allow to separate the connected high-frequency vibration measurements as well. Applying the novel feature selection technique of the authors, the basis for the vibration based micro-milling tool condition monitoring for ceramics cutting is presented for different toolpath strategies. It resulted in the identification of the most relevant vibration signal features and the presentation of the identified and automatically separated tool wearing stages as well.

Author Biographies

Zsolt János Viharos, Centre of Excellence in Production Informatics and Control, Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH); John von Neumann University

Research Laboratory on Engineering and Management Intelligence, Leader of the Intelligent Processes Research Group, senior research fellow;

John von Neumann University, lecturer

László Móricz, Zalaegerszeg Center of Vocational Training, lecturer

Researcher

Máté István Büki, Centre of Excellence in Production Informatics and Control, Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH);

Research Laboratory on Engineering and Management Intelligence, Intelligent Processes Research Group, part time student researcher

Downloads

Additional Files

Published

2021-09-30

Issue

Vol. 10 No. 3 (2021)

Section

Research Papers

License

Authors who publish with this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).