STRING (Satuan Tulisan Riset dan Inovasi Teknologi)
Vol 2, No 2 (2017)

Deteksi Cacat Plate Insulator Menggunakan Backpropagation Neural Network

Agung Ferdinan Sandy (Program Studi Informatika, Universitas Indraprasta PGRI)



Article Info

Publish Date
09 Dec 2017

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 imagingĀ  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.

Copyrights © 2017






Journal Info

Abbrev

STRING

Publisher

Subject

Computer Science & IT Mathematics

Description

STRING (Satuan Tulisan Riset dan Inovasi Teknologi) focuses on the publication of the results of scientific research related to the science and technology. STRING publishes scholarly articles in Science and Technology Focus and Scope Covering: 1. Computing and Informatics 2. Industrial Engineering ...