Improving OEE Data Quality By Automated Data Collection Through Identifying Productivity Potentials

Karuppiah, K.Vasanthan (2016) Improving OEE Data Quality By Automated Data Collection Through Identifying Productivity Potentials. Masters thesis, Universiti Teknikal Malaysia Melaka.

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Abstract

Most semiconductor organizations take after the SEMI standard rules to gauge equipment availability and utilization by means of Overall Equipment Effectiveness (OEE).Be that as it may,a few issues should be vanquished to get improve data accuracy of OEE.For instance,the time interims of OEE losses are basic to the improvement studies,however it is difficult to gather reliable and precise information.Hence,people will find the obscure contrasts between the manual recorded losses from their operational system and OEE losses from SEMI standard definition once people execute OEE.Besides,how to acquire the every stoppages of machine in real time to determine equipment stability issued to be conquered.This project is to develop an IT integrate framework to record the equipment process state for the bottleneck process "wire bonder" in the semiconductor assembly industry. Semiconductor equipment interface protocol for equipment to host communication (SECS/GEM) and Manufacturing Execution System (MES) into an Automated Data Collection framework for gathering valuable information.The information quality is further assurance by the real time detection of equipment status from the automate data collection framework.The application of the automate data collection framework is get rid of the unknown OEE losses.This will resolves the accuracy and timeliness issue associated with manual gathering OEE information.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Total productive maintenance,Industrial equipment
Subjects: T Technology > T Technology (General)
T Technology > TS Manufactures
Divisions: Library > Tesis > FKP
Depositing User: Mohd. Nazir Taib
Date Deposited: 11 Jul 2018 03:00
Last Modified: 11 Jul 2018 03:00
URI: http://eprints.utem.edu.my/id/eprint/20972
Statistic Details: View Download Statistic

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