Automated vision system to improve inspection lead time for molded components based on neural network

This research studies on the improvement on the traditional visual inspection method where in this thesis the manual visual inspection system will be improved to an automated visual inspection system with the aid of neural-network.This is to avoid molding defects to escape to customers and reduce th...

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Main Author: Nandagopal, Darvind Kumar
Format: Thesis
Language:English
English
Published: 2023
Online Access:http://eprints.utem.edu.my/id/eprint/27359/1/Automated%20vision%20system%20to%20improve%20inspection%20lead%20time%20for%20molded%20components%20based%20on%20neural%20network.pdf
http://eprints.utem.edu.my/id/eprint/27359/2/Automated%20vision%20system%20to%20improve%20inspection%20lead%20time%20for%20molded%20components%20based%20on%20neural%20network.pdf
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spelling my-utem-ep.273592024-05-30T12:13:43Z Automated vision system to improve inspection lead time for molded components based on neural network 2023 Nandagopal, Darvind Kumar This research studies on the improvement on the traditional visual inspection method where in this thesis the manual visual inspection system will be improved to an automated visual inspection system with the aid of neural-network.This is to avoid molding defects to escape to customers and reduce the production lead time.This is because the manual visual inspection is prone to human errors.Therefore, there is a need of intellingent visual inspection method which reduces the reject escapee and also improves on the lead time.The objective of this thesis is to detect the critical defects that could be inspected using automated visual inspection. Moreover, this developed system should be able to detect defect on the molded package. In addition to that, the performance of this developed system is evaluated based on the reduction on the lead time and the effectiveness of the defect detection.Thus, the neural network method is used for defect detection and also to automated the system which aids in improving the lead time.The developed system achieves the objectives by reducing escapee by eliminating outgoing quality assurance detection which means 0 customer complain on molding defects. This also proves that the developed system have 0 escape rate to customers.This system also reduces the lead time from 57 minuted to 32 minutes which means 43.86% reduction on lead time.Moreover, the cost saving for 5 years for the developed system is RM 157500.00.Therefore, as a conclusion the developed system achieves the objectives set by able to identify critical defects which it is able to detect the defects for molded package which improves the visual system effectiveness and also reduces the lead time. 2023 Thesis http://eprints.utem.edu.my/id/eprint/27359/ http://eprints.utem.edu.my/id/eprint/27359/1/Automated%20vision%20system%20to%20improve%20inspection%20lead%20time%20for%20molded%20components%20based%20on%20neural%20network.pdf text en public http://eprints.utem.edu.my/id/eprint/27359/2/Automated%20vision%20system%20to%20improve%20inspection%20lead%20time%20for%20molded%20components%20based%20on%20neural%20network.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=123199 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering Md Fauadi, Muhammad Hafidz Fazli
institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Md Fauadi, Muhammad Hafidz Fazli
description This research studies on the improvement on the traditional visual inspection method where in this thesis the manual visual inspection system will be improved to an automated visual inspection system with the aid of neural-network.This is to avoid molding defects to escape to customers and reduce the production lead time.This is because the manual visual inspection is prone to human errors.Therefore, there is a need of intellingent visual inspection method which reduces the reject escapee and also improves on the lead time.The objective of this thesis is to detect the critical defects that could be inspected using automated visual inspection. Moreover, this developed system should be able to detect defect on the molded package. In addition to that, the performance of this developed system is evaluated based on the reduction on the lead time and the effectiveness of the defect detection.Thus, the neural network method is used for defect detection and also to automated the system which aids in improving the lead time.The developed system achieves the objectives by reducing escapee by eliminating outgoing quality assurance detection which means 0 customer complain on molding defects. This also proves that the developed system have 0 escape rate to customers.This system also reduces the lead time from 57 minuted to 32 minutes which means 43.86% reduction on lead time.Moreover, the cost saving for 5 years for the developed system is RM 157500.00.Therefore, as a conclusion the developed system achieves the objectives set by able to identify critical defects which it is able to detect the defects for molded package which improves the visual system effectiveness and also reduces the lead time.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Nandagopal, Darvind Kumar
spellingShingle Nandagopal, Darvind Kumar
Automated vision system to improve inspection lead time for molded components based on neural network
author_facet Nandagopal, Darvind Kumar
author_sort Nandagopal, Darvind Kumar
title Automated vision system to improve inspection lead time for molded components based on neural network
title_short Automated vision system to improve inspection lead time for molded components based on neural network
title_full Automated vision system to improve inspection lead time for molded components based on neural network
title_fullStr Automated vision system to improve inspection lead time for molded components based on neural network
title_full_unstemmed Automated vision system to improve inspection lead time for molded components based on neural network
title_sort automated vision system to improve inspection lead time for molded components based on neural network
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty of Manufacturing Engineering
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/27359/1/Automated%20vision%20system%20to%20improve%20inspection%20lead%20time%20for%20molded%20components%20based%20on%20neural%20network.pdf
http://eprints.utem.edu.my/id/eprint/27359/2/Automated%20vision%20system%20to%20improve%20inspection%20lead%20time%20for%20molded%20components%20based%20on%20neural%20network.pdf
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