Widyarto Nugroho, Erdhi and sri widodo, Thomas and litasari, Litasari Pemakaian Jaringan Saraf Tiruan Untuk Mendeteksi Kesalahan Printed Circuit Board (PCB). Proseding Seminar Nasional Riset Teknologi Informasi 2008,AKAKOM, 9 Agustus 2008.
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Abstract
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
Item Type: | Article |
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Subjects: | 000 Computer Science, Information and General Works > 005 Computer programming, programs & data > Information Systems |
Depositing User: | Mr. Erdhi Widyarto |
Date Deposited: | 22 Nov 2016 11:34 |
Last Modified: | 23 Dec 2019 12:25 |
URI: | http://repository.unika.ac.id/id/eprint/12618 |
Available Versions of this Item
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Pemakaian Jaringan Saraf Tiruan Untuk Mendeteksi Kesalahan Printed Circuit Board (PCB). (deposited 26 Jan 2016 22:17)
- Pemakaian Jaringan Saraf Tiruan Untuk Mendeteksi Kesalahan Printed Circuit Board (PCB). (deposited 22 Nov 2016 11:34) [Currently Displayed]
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