International Journal of Engineering and Technology

Multivariate statistical techniques were applied to identify the behavior of physicochemical parameters on calorific value in oil samples used in the industrial petrochemical sector of Mamonal in Cartagena de indias, Colombian Caribbean. Initially a physicochemical characterization of the samples was carried out through a principal components analysis, then a cluster analysis to identify similarities between the samples and to have a better description of the samples and finally a multiple regression model is fitted to determine the physicochemical factors that influence In the behavior of the calorific value of the oil samples. The results show that there are different associations between the physicochemical parameters; The cluster analysis yielded 4 groups of oil samples with different physicochemical behaviors and according to the criterion of loss of AIC information in the linear regression model, samples with low sulfur, sodium and ash content and high zinc content, Phosphorus and chlorine contribute to the increase of calorific value in the samples.