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Improving oil classification quality from oil spill fingerprint beyond six sigma approach.

Authors :
Juahir H
Ismail A
Mohamed SB
Toriman ME
Kassim AM
Zain SM
Ahmad WKW
Wah WK
Zali MA
Retnam A
Taib MZM
Mokhtar M
Source :
Marine pollution bulletin [Mar Pollut Bull] 2017 Jul 15; Vol. 120 (1-2), pp. 322-332. Date of Electronic Publication: 2017 May 20.
Publication Year :
2017

Abstract

This study involves the use of quality engineering in oil spill classification based on oil spill fingerprinting from GC-FID and GC-MS employing the six-sigma approach. The oil spills are recovered from various water areas of Peninsular Malaysia and Sabah (East Malaysia). The study approach used six sigma methodologies that effectively serve as the problem solving in oil classification extracted from the complex mixtures of oil spilled dataset. The analysis of six sigma link with the quality engineering improved the organizational performance to achieve its objectivity of the environmental forensics. The study reveals that oil spills are discriminated into four groups' viz. diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) according to the similarity of the intrinsic chemical properties. Through the validation, it confirmed that four discriminant component, diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) dominate the oil types with a total variance of 99.51% with ANOVA giving F <subscript>stat</subscript> >F <subscript>critical</subscript> at 95% confidence level and a Chi Square goodness test of 74.87. Results obtained from this study reveals that by employing six-sigma approach in a data-driven problem such as in the case of oil spill classification, good decision making can be expedited.<br /> (Copyright © 2017. Published by Elsevier Ltd.)

Details

Language :
English
ISSN :
1879-3363
Volume :
120
Issue :
1-2
Database :
MEDLINE
Journal :
Marine pollution bulletin
Publication Type :
Academic Journal
Accession number :
28535957
Full Text :
https://doi.org/10.1016/j.marpolbul.2017.04.032