แจ้งเอกสารไม่ครบถ้วน, ไม่ตรงกับชื่อเรื่อง หรือมีข้อผิดพลาดเกี่ยวกับเอกสาร ติดต่อที่นี่ ==>
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
Thongchart Kerdphol. Microscale quality inspection with artificial intelligence in the manufacturing process of void coil magnet assembly. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2024.
Microscale quality inspection with artificial intelligence in the manufacturing process of void coil magnet assembly
Name: Kreetiwat Chaiyasin
Organization :
Suranaree University of Technology. Mechatronic Engineering
Name: Kitsana Khodcharad
Organization :
Suranaree University of Technology. Mechatronic Engineering
Name: Veena Phunpeng
Organization :
Suranaree University of Technology. Mechatronic Engineering
Name: Thongchart Kerdphol
Organization :
Kasetsart University. Faculty Of Engineering
Email :
kreetiwat.k@gmail.com
keyword:
VCMA
LCSH:
Artificial intelligence
LCSH:
Quality control
Abstract:
In today's rapidly evolving manufacturing industry, product quality control is critical, especially in sectors requiring high precision, such as automotive, electronics, and semiconductors. Traditional quality inspection methods, which rely on manual labor, continue to face limitations in detecting complex and small-scale defects, potentially impacting product reliability and organizational reputation. To address these challenges, this research applies Artificial Intelligence (AI) and Machine Learning (ML) technologies, specifically focusing on the Void Coil Magnet Assembly (VCMA) in electronic device production. The study utilizes YOLOv5 for real-time object detection of dust particles and ResNet50 for detailed image classification to enhance defect detection accuracy. The models were trained on high-resolution images of VCMA components, with data augmentation techniques applied to improve model robustness. Results indicate that YOLOv5 achieves a precision of 67.6% but has a lower recall (54.5%), making it suitable for initial screenings in fast-paced environments. In contrast, ResNet50 demonstrates high precision (91%) and recall (90%), proving effective for comprehensive inspections where accuracy is paramount. This research highlights the potential of AI to improve quality inspection processes, comparing AI-based methods to traditional approaches and showcasing its application across various industries.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2024
Modified:
2025-08-19
Issued:
2025-08-19
บทความ/Article
application/pdf
BibliograpyCitation :
In Thai Society of Mechanical Engineers (TSME) and Kasetsart University (KU). The 14th TSME International Conference on Mechanical Engineering (TSME-ICoME14 2024) (DRC0013). Chonburi : Kasetsart University Sriracha Campus, 2024
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
ใช้เวลา
0.021771 วินาที
Kreetiwat Chaiyasin
| Title | Contributor | Type |
|---|---|---|
| Evaluation of the behavior of sandwich composite structures reinforced with flax fiber and flexible cores
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kitsana Khodcharad;Kreetiwat Chaiyasin;Wipada Boransan;Watcharapong Patangtalo;Veena Phunpeng | บทความ/Article | |
| Microscale quality inspection with artificial intelligence in the manufacturing process of void coil magnet assembly
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kreetiwat Chaiyasin;Kitsana Khodcharad;Veena Phunpeng;Thongchart Kerdphol | บทความ/Article |
Kitsana Khodcharad
| Title | Contributor | Type |
|---|---|---|
| Evaluation of the behavior of sandwich composite structures reinforced with flax fiber and flexible cores
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kitsana Khodcharad;Kreetiwat Chaiyasin;Wipada Boransan;Watcharapong Patangtalo;Veena Phunpeng | บทความ/Article | |
| Microscale quality inspection with artificial intelligence in the manufacturing process of void coil magnet assembly
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kreetiwat Chaiyasin;Kitsana Khodcharad;Veena Phunpeng;Thongchart Kerdphol | บทความ/Article |
Veena Phunpeng
| Title | Contributor | Type |
|---|---|---|
| Evaluation of the behavior of sandwich composite structures reinforced with flax fiber and flexible cores
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kitsana Khodcharad;Kreetiwat Chaiyasin;Wipada Boransan;Watcharapong Patangtalo;Veena Phunpeng | บทความ/Article | |
| Microscale quality inspection with artificial intelligence in the manufacturing process of void coil magnet assembly
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kreetiwat Chaiyasin;Kitsana Khodcharad;Veena Phunpeng;Thongchart Kerdphol | บทความ/Article |
Thongchart Kerdphol
| Title | Contributor | Type |
|---|---|---|
| Small-signal stability analysis in an uncertain microgrid with distributed energy resources : a data-driven monitoring
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Watcharakorn Pinthurat;Tossaporn Surinkaew;Thongchart Kerdphol;Boonruang Marungsri | บทความ/Article | |
| Design of community hydropower storage for agriculture in Thailand\'s highland area
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Wech Oramoot;Rachata Sucholpanit;Nottakorn Sukmanont;Dhamrongsak Khakkharho;Pongsakorn Anantarativakorn;Junlachat Sanjaisue;Nidchabendha Chandanachulaka Roekrai;Thongchart Kerdphol | บทความ/Article | |
| Microscale quality inspection with artificial intelligence in the manufacturing process of void coil magnet assembly
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kreetiwat Chaiyasin;Kitsana Khodcharad;Veena Phunpeng;Thongchart Kerdphol | บทความ/Article | |
| Predictive of ground source heat pump energy efficiency based on time series neural network approach
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Tanaboon Thongveroj;Kanet Katchasuwanmanee;Apiniti Jotisankasa;Attaporn Wisessint;Thongchart Kerdphol;Cheema Soralump;Peerayot Sanposh;Sorawit Limthongkul;Siwakorn Chuensiri | บทความ/Article |