Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal STRING (Satuan Tulisan Riset dan Inovasi Teknologi)
Agung Ferdinan Sandy
Program Studi Informatika, Universitas Indraprasta PGRI
Computer Science & IT Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Deteksi Cacat Plate Insulator Menggunakan Backpropagation Neural Network Agung Ferdinan Sandy
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 2, No 2 (2017)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (649.498 KB) | DOI: 10.30998/string.v2i2.2109

Abstract

Visual Inspection Plate Insulator Check is a critical step of quality control to ensure materials used are pass quality standard. The problem of manual material inspection can not detect whether the materials used for production are fine (OK) or not good (NG). Because of the failure in the inspection, there will be material and manpower loss due to rejection. In addition, it may make more problems if this defect product (NG) is delivered to customer. Then, it will jeropardize the company credibility. The problem of inspection failure can happen because of human factor such as tired, inaccurate, low-skill operator inspection with visual check. Therefore in this study, the researcher will develop a visual inspection technique of material checking with imaging  processing backpropagation neural network. Using image processing technique, the differences between OK materials and NG material will be investigated from the both images. The product images will be captured in production line and the comparison will be observed with the OK product. It is expected, this inspection will be more accurate and does not depend on human factors. Finally, the technique can be developed further into automatic visual inspection by material checking, e.g. a kind of Plastic.
Co-Authors