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Process Improvement Through Six Sigma Methodology - Mv Machine Defective Reduction


Citation

Muid, Zalizan (2000) Process Improvement Through Six Sigma Methodology - Mv Machine Defective Reduction. Masters thesis, Universiti Putra Malaysia.

Abstract

Six Sigma tools and methodologies have innovated a solution for quality improvement. In Auto Mount Department of Sony Technology Malaysia in Bangi, Selangor, MY machine defective reduction project was performed as part of quality improvement efforts. Six Sigma tools and methodology were employed to conduct this project. This involved four simple but rigorous steps called Measure-Analyze-Improve-Control (MAlC) where tools such as Process Map, Measurement System Analysis (MSA), Cause and Effect Diagram, Failure Mode and Effect Analysis (FMEA), Fault Tree Analysis (FT A), Design of Experiment (DOE) and Statistical Process Control (SPC) were used. The objective was to obtain knowledge about sources of variability that cause the defects and then to improve process capability to attain Six Sigma capability. The sources of variability are the machine input factors such as nozzle, z-carriage, feeder cassette, XY table and head unit to generate corresponding outputs (i.e. defectives). Upon identifying the variables, actions were taken to eliminate and to control the identified variability contributors. The project provides excellent insight into the power of Six Sigma as a process improvement tools. It provides significant process knowledge based on facts and data and facilitates the information sharing. As a result, the machine improved by more than 50%, which accounts for the annual savings of more than RM50,000.


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Additional Metadata

Item Type: Thesis (Masters)
Subject: Production management
Subject: Quality control - Statistical methods
Call Number: FK 2000 41
Chairman Supervisor: Ir. Haji Mohd Rasid Osman
Divisions: Faculty of Engineering
Depositing User: Nur Kamila Ramli
Date Deposited: 04 May 2011 02:55
Last Modified: 04 Apr 2024 01:07
URI: http://psasir.upm.edu.my/id/eprint/10526
Statistic Details: View Download Statistic

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