Novel and Cost-Effective CNC Tool Condition Monitoring Through Image Processing Techniques

Novel and Cost-Effective CNC Tool Condition Monitoring Through Image Processing Techniques | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Novel and Cost-Effective CNC Tool Condition Monitoring Through Image Processing Techniques Alireza Falah, Mátyás Andó This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4777691/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract This paper introduces a novel and effective approach for tool condition monitoring (TCM) in CNC machining through the application of image processing techniques. Utilizing a consumer-grade camera capable of recording videos at 60 frames per second, the study demonstrates a cost-effective method for detecting tool breakage and identifying edge fractures. Basic image processing techniques, including frame extraction, background subtraction, thresholding, and morphological operations, are applied to analyze the captured images and videos. This research not only offers a practical solution to enhance the efficiency and accuracy of CNC machine operations but also aligns with advancements in smart manufacturing and Industry 4.0. Moreover, it paves the way for future research in this area, suggesting potential for further refinement and broader application of such monitoring techniques. CNC Tool Monitoring Image Processing Machine Vision Smart Manufacturing Predictive Maintenance. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 06 Aug, 2024 Reviewers agreed at journal 05 Aug, 2024 Reviewers agreed at journal 05 Aug, 2024 Reviewers agreed at journal 05 Aug, 2024 Reviews received at journal 04 Aug, 2024 Reviews received at journal 02 Aug, 2024 Reviewers agreed at journal 01 Aug, 2024 Reviewers agreed at journal 01 Aug, 2024 Reviewers agreed at journal 31 Jul, 2024 Reviewers invited by journal 31 Jul, 2024 Editor assigned by journal 31 Jul, 2024 Submission checks completed at journal 30 Jul, 2024 First submitted to journal 21 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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