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|Title:||A Big Data Application in Manufacturing Industry-Computer Vision to Detect Defects on Bearings||Authors:||Ünal, P.
Özbayoğlu, A. Murat
image classification with localization
Big data applications
Image classification with localization
Loss of time
|Issue Date:||2022||Publisher:||Institute of Electrical and Electronics Engineers Inc.||Abstract:||In the contemporary rotating machinery, bearings are critical and indispensable parts. Early detection of rolling bearing defects carries crucial importance, because undetected defects on the rolling bearings may end in loss of time, resources, money and even lives. In parallel to the accelerated utilization of deep learning applications in the manufacturing industry, different studies have been conducted to determine and evaluate defects on the surfaces of rolling bearings. In this study, a new system, that contains a hardware platform and software components in order to detect surface defects of the metal rolling bearings has been developed. To detect defects, optic image data of the bearings were used, and then computer vision and artificial intelligence techniques were applied to them. In the system, TC-VISION, the source of big data is the platform designed and developed using the optical camera. The results of the applied CNN algorithms performed better than the targeted values with respect to several metrics. The F1 score obtained is close to 100%. The developed system is aimed to be enhanced further in order to develop a fully automated inspection and quality control system for metal rolling bearing systems appropriate for serial production in real industrial environments. © 2022 IEEE.||Description:||Ankura;et al.;Hitachi;KPMG Consulting Co., Ltd.;NTT Data Intellilink Corporation;Think in Data Initiative, Association Inc
2022 IEEE International Conference on Big Data, Big Data 2022 -- 17 December 2022 through 20 December 2022 -- 186390
|Appears in Collections:||Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection|
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checked on May 29, 2023
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