diagnostics technologies of cutting tools with cnc equipment

Clicks: 237
ID: 137258
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Star

Ranked #53 of 82 articles by views in artificial cells, nanomedicine and biotechnology

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Productivity of modern machine tools depends mostly on the cutting tool condition. One of the most complicated manufacturing process in metal cutting is a surface milling. The lack of effective tools for rapid assessment of cutter wear causes its damage or reduction in working accuracy, and leads to faulty production and the loss of working time. The article provides the overview of existing methods of the cutting tool diagnostics.
Reference Key
vereshchagin2016uenyediagnostics Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Mr. Vladislav Y. Vereshchagin;Ms. Alexandra S. Vereshchagina;Ms. Elena G. Kravchenko
Journal artificial cells, nanomedicine and biotechnology
Year 2016
DOI
10.17084/2016.II-1(26).7
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.