Pemakaian Jaringan Saraf Tiruan Untuk Mendeteksi Kesalahan Printed Circuit Board (PCB)
| Main Authors: | Widyarto Nugroho, Erdhi, sri widodo, Thomas, litasari, Litasari |
|---|---|
| Format: | Article PeerReviewed Book |
| Bahasa: | eng |
| Subjects: | |
| Online Access: |
http://repository.unika.ac.id/12618/1/PCB.pdf http://repository.unika.ac.id/12618/ |
Daftar Isi:
- in mass production printed circuit board (PCB) manufacturing, sometimes PCB gets defects. manual inspection is slow, and does not assure high quality.this research aim is search and analysis using artificial neural network to defect PCB inspection.to determining characteristic of defect PCB is used Euler number, boundary and circle drill the defects PCB pattern to be investigated are spurs,break,short, hole, breakdown, overetch, underetch, wrong size hole, island and mouse bite. determining characteristic of each defect PCB pattern to get data trained. this data is trained for artificial neural network by backpropagation method. then neural network models is used defect PCB inspection. this result of research indicate that artificial neural network can detect defect PCB pattern and Euler number, boundary and circle drill can used for determining characteristic