DMAIC Six Sigma Methodology in Petroleum Hydrocarbon Oil Classification

Abstract

This research focuses on the use of the DMAIC method (Define, Measure, Analyze, Improve and Control) as a Six Sigma approach in studying oil spill fingerprint of samples recovered from Peninsular Malaysia and Sabah (East Malaysia). The DMAIC approach in this study was used as a way to classify oil types based on data obtained from GC-FID and GC-MS measurements. The cause-effect diagram was used to define the factors leading to the failure of the oil spill fingerprinting based on inaccurate oil type clustering. Discriminant Analysis (DA) was also applied to quantify the root-cause of the failure. An Ishikawa diagram obtained in the analysis phase identifies the potential failure causal. Principal component analysis (PCA) was applied and was successful in discriminating four clusters of oil types, namely diesel, heavy fuel oil (HFO), mixture oil lube and fuel oil (MOLFO) and waste oil (WO) with a total variance of 85.3%. In the control phase, the use of a Pareto chart indicated 100% cumulative percentage of oil type clustering with a 95% confidence level. The DMAIC approach to be effective in solving oil spill fingerprinting problems and results in quality improvement in the clustering of oil spills into the different hydrocarbon types.