DOI: 10.1016/j.marpolbul.2017.04.032
Scopus记录号: 2-s2.0-85019851981
论文题名: Improving oil classification quality from oil spill fingerprint beyond six sigma approach
作者: Juahir H. ; Ismail A. ; Mohamed S.B. ; Toriman M.E. ; Kassim A.M. ; Zain S.M. ; Ahmad W.K.W. ; Wah W.K. ; Zali M.A. ; Retnam A. ; Taib M.Z.M. ; Mokhtar M.
刊名: Marine Pollution Bulletin
ISSN: 0025-326X
EISSN: 1879-3363
出版年: 2017
卷: 120, 期: 2018-01-02 起始页码: 322
结束页码: 332
语种: 英语
英文关键词: Fingerprinting
; Hydrocarbon
; Oil classification
; Quality engineering
; Six-sigma
Scopus关键词: Classification (of information)
; Decision making
; Forensic engineering
; Fuel oils
; Fuels
; Hydrocarbons
; Mixtures
; Oil spills
; Problem solving
; Process monitoring
; Six sigma
; Work simplification
; Data-driven problems
; Environmental forensics
; Fingerprinting
; Oil classification
; Organizational performance
; Quality engineering
; Six sigma approaches
; Six-Sigma methodology
; Process engineering
; diesel fuel
; fuel oil
; hydrocarbon
; lubricating agent
; classification
; diesel
; engineering
; hydrocarbon
; lubricant
; oil spill
; qualitative analysis
; Article
; classification
; concentration (parameters)
; controlled study
; environmental parameters
; Malaysia
; oil spill
; quality control
; quality engineering
; six sigma approach
; analysis
; mass fragmentography
; oil spill
; total quality management
; Malaysia
; West Malaysia
; Fuel Oils
; Gas Chromatography-Mass Spectrometry
; Malaysia
; Petroleum Pollution
; Total Quality Management
Scopus学科分类: Agricultural and Biological Sciences: Aquatic Science
; Earth and Planetary Sciences: Oceanography
; Environmental Science: Pollution
英文摘要: 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. © 2017 Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/88064
Appears in Collections: 过去全球变化的重建 全球变化的国际研究计划
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作者单位: East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin, Gong Badak Campus, Kuala Terengganu, Malaysia; Faculty of Design, Innovation and Technology (FRIT), Universiti Sultan Zainal Abidin, Gong Badak Campus, Kuala Terengganu, Malaysia; Environmental Health Division, Department of Chemistry Malaysia, Ministry of Science, Technology and Innovation, Jalan Sultan, Petaling Jaya, Selangor, Malaysia; Chemistry Department, University of Malaya, Kuala Lumpur, Malaysia; Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia; Integrated Envirotech Sdn. Bhd., 32-2, Jalan Setiawangsa 11A, Setiawangsa, Kuala Lumpur, Malaysia
Recommended Citation:
Juahir H.,Ismail A.,Mohamed S.B.,et al. Improving oil classification quality from oil spill fingerprint beyond six sigma approach[J]. Marine Pollution Bulletin,2017-01-01,120(2018-01-02)