Improving the quality assessment of drilled holes in aircraft structures

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This study proposes a neural network method for assessing drilled hole quality in aircraft structures by analyzing electric current data, aiming to improve efficiency and reduce inspections.

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This paper presents a case study in an aircraft structure assembly cell, evaluating automated drilling quality using data from monitoring the electric current consumed by the drilling system drive. The authors propose an indicator of final drilled-hole quality computed with a committee of neural networks trained to analyze the current-monitoring signals, aiming to streamline production by reducing the need for additional measurement steps and physical inspections that increase cycle time. The stated caveat is that the work is presented as a case study/preprint and is explicitly not peer reviewed in that version, limiting generalizability beyond the reported setup. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

This paper presents a case study carried out in an assembly cell where automated drilling of an aeronautical structure is performed. The study shows how techniques approached by the 4.0 industry have the potential to contribute to manufacturing, breaking the limits imposed by the previous state of the art systems. This paper proposes a method capable of calculating an indicator for the final quality of the drilled holes, by using a committee of neural networks, which analyses data obtained by monitoring the electric current consumed by the drilling system drive. The method has the potential to enhance the efficiency of the drilling process, avoiding measurement steps and physical inspections that increases the cell cycle time.The proposal contributes to the literature by presenting an unprecedented application and to the praxis by solving a relevant problem of the aerospace industry.
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Improving the quality assessment of drilled holes in aircraft structures | 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 Improving the quality assessment of drilled holes in aircraft structures Frederico Leoni Franco Kawano, Claudio Fabiano Motta Toledo, Gustavo Franco Barbosa, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2705166/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Jul, 2023 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 3 You are reading this latest preprint version Abstract This paper presents a case study carried out in an assembly cell where automated drilling of an aeronautical structure is performed. The study shows how techniques approached by the 4.0 industry have the potential to contribute to manufacturing, breaking the limits imposed by the previous state of the art systems. This paper proposes a method capable of calculating an indicator for the final quality of the drilled holes, by using a committee of neural networks, which analyses data obtained by monitoring the electric current consumed by the drilling system drive. The method has the potential to enhance the efficiency of the drilling process, avoiding measurement steps and physical inspections that increases the cell cycle time.The proposal contributes to the literature by presenting an unprecedented application and to the praxis by solving a relevant problem of the aerospace industry. neural networks precision holes aircraft structures advanced manufacturing Full Text Cite Share Download PDF Status: Published Journal Publication published 25 Jul, 2023 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Reviewers agreed at journal 20 Mar, 2023 Editor assigned by journal 19 Mar, 2023 First submitted to journal 17 Mar, 2023 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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