Academic Journal

AI-based Bubbles Detection in the Conformal Coating for Enhanced Quality Control in Electronics Manufacturing

التفاصيل البيبلوغرافية
العنوان: AI-based Bubbles Detection in the Conformal Coating for Enhanced Quality Control in Electronics Manufacturing
المؤلفون: Zouhri, Nizar, Mourabit, Aimad El, Abidine, Alaoui Ismaili Zine El
المصدر: Journal of Robotics and Control (JRC); Vol 5, No 2 (2024); 525-532 ; 2715-5072 ; 2715-5056 ; 10.18196/jrc.v5i2
بيانات النشر: Universitas Muhammadiyah Yogyakarta
سنة النشر: 2024
المجموعة: Leading & Enlightening Journal UMY (Universitas Muhammadiyah Yogyakarta)
مصطلحات موضوعية: Artificial Intelligence, Bubble Detection, Conformal Coatings, Quality Control, Machine Learning, Deep Learning, Edge AI, Industry Standardization
الوصف: This research pioneers the application of artificial intelligence (AI) methodologies—machine learning, deep learning, hybrid models, transfer learning, and edge AI deployment—in enhancing bubble detection within conformal coatings, a critical as- pect of electronics manufacturing quality control. By addressing the limitations of traditional detection methods, our work offers a novel approach that significantly improves automation, accuracy, and speed, thereby ensuring the reliability of electronic assemblies and contributing to economic and safety benefits. We navigate through the challenges of creating diverse datasets, system robustness, and the imperative for industry-wide standardization, proposing strategies for overcoming these obstacles. Our findings highlight the transformative impact of AI on quality control processes, demonstrating substantial advancements in detection capabilities. Furthermore, we advocate for future research, development, and collaboration to extend these AI-driven improvements across the manufacturing spectrum. This study underscores the potential of AI to revolutionize electronics manufacturing, emphasizing the need for continued innovation and standardization to realize safer, more efficient, and cost-effective production methodologies.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
Relation: https://journal.umy.ac.id/index.php/jrc/article/view/20441/9050; https://journal.umy.ac.id/index.php/jrc/article/view/20441
DOI: 10.18196/jrc.v5i2.20441
الاتاحة: https://journal.umy.ac.id/index.php/jrc/article/view/20441
https://doi.org/10.18196/jrc.v5i2.20441
Rights: Copyright (c) 2024 Nizar Zouhri, Aimad El Mourabit, Alaoui Ismaili Zine El Abidine ; https://creativecommons.org/licenses/by-sa/4.0
رقم الانضمام: edsbas.AF703AC0
قاعدة البيانات: BASE