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

Hafizan Juahir, Azimah Ismail, Saiful Bahri Mohamed, Mohd. Ekhwan Toriman, Azlina Md Kassim, Sharifuddin Md Zain, Wan Kamaruzaman Wan Ahmad, Wong Kok Wah, Munirah Abdul Zali, Ananthy Retnam, Mohd Zaki Mohd Taib, Mazlin Mokhtar

Research output: Contribution to journalArticle

3 Citations (Scopus)

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 Fstat >Fcritical 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.

Original languageEnglish
JournalMarine Pollution Bulletin
DOIs
Publication statusAccepted/In press - 7 Feb 2017

Fingerprint

oil spills
Oil spills
oil spill
fuel oils
oils
Fuel oils
oil
lubricant
lubricants
diesel
hydrocarbon
Malaysia
engineering
Lubricants
hydrocarbons
Hydrocarbons
chemical property
Borneo
Analysis of variance (ANOVA)
decision making

Keywords

  • Fingerprinting
  • Hydrocarbon
  • Oil classification
  • Quality engineering
  • Six-sigma

ASJC Scopus subject areas

  • Oceanography
  • Aquatic Science
  • Pollution

Cite this

Improving oil classification quality from oil spill fingerprint beyond six sigma approach. / Juahir, Hafizan; Ismail, Azimah; Mohamed, Saiful Bahri; Toriman, Mohd. Ekhwan; Kassim, Azlina Md; Zain, Sharifuddin Md; Ahmad, Wan Kamaruzaman Wan; Wah, Wong Kok; Zali, Munirah Abdul; Retnam, Ananthy; Taib, Mohd Zaki Mohd; Mokhtar, Mazlin.

In: Marine Pollution Bulletin, 07.02.2017.

Research output: Contribution to journalArticle

Juahir, Hafizan ; Ismail, Azimah ; Mohamed, Saiful Bahri ; Toriman, Mohd. Ekhwan ; Kassim, Azlina Md ; Zain, Sharifuddin Md ; Ahmad, Wan Kamaruzaman Wan ; Wah, Wong Kok ; Zali, Munirah Abdul ; Retnam, Ananthy ; Taib, Mohd Zaki Mohd ; Mokhtar, Mazlin. / Improving oil classification quality from oil spill fingerprint beyond six sigma approach. In: Marine Pollution Bulletin. 2017.
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