**2. Application: Oil refining**

4 Multivariate Analysis in Management, Engineering and the Sciences

correlated responses in a manufacturing process.

laboratory equipment.

sequence.

ANN was superior.

Metaheuristic.

Bao and Dai (2009) studied different multivariate methods, including linear and nonlinear techniques in order to minimize the error of prediction by models developed for quality control of gasoline. Lira et al. (2010) applied the PLS method for inference of the quality parameters: density, sulfur concentration and distillation temperatures of the mixture diesel / bio-diesel, providing great savings in time compared with the traditional methods by

Aleme, Corgozinho and Barbeira (2010) have conducted a study of classification of samples using the PCA method for discrimination of diesel oil type and the prediction of their origin. Paiva Ferreira and Balestrassi (2007) have combined the Response Surface Method (RSM) of Design of Experiments (DOE) with Principal Component Analysis in optimizing multiple

Huang, Hsu and Liu (2009) have used Mahalanobis-Taguchi integrated with Artificial Neural Networks in data mining to look for patterns and modeling in manufacturing. Pal and Maiti (2010) have adopted the Mahalanobis-Taguchi algorithm to reduce the dimensionality of multivariate data and for optimization with Metaheuristics in the

Liu et al. (2007) have made inferences about quality parameters of jet fuel using Multiple Linear Regression (MLR) and ANN. The work showed that the performance of modeling by

In optimization of multivariate models, there are applications combined with Multivariate Analysis of Metaheuristics, such as simulated annealing (SAUNIER, et al., 2009), genetic algorithm (GA) (Roy, Roy, 2009) tabu search (QI; SHI; KONG, 2010), particle swarm (Pal;

With the objective of optimizing the dimensionality of multivariate models and avoid the overfitting phenomenon in determining principal components, Xu and Liang (2001) have used the Monte Carlo Simulation on simulated data sets and two real cases. Gourvénec et al. (2003) compared Monte Carlo cross-validation with the traditional method of cross

Adler e Yazhemsky (2010) have combined the Monte Carlo Simulation, PCA and Data Envelopment Analysis (DEA) in a context where there is a relatively large number of variables related to the number of observations for decision making. Llobet et al. (2005), by means a Multiple Criteria Decision-Making (MCDM) model, have used Fuzzy classification of samples of chips. For prediction oxidative and hydrolytic properties, was used an electronic nose based on PLS models, with prior selection of input variables by a GA

Wu, Feng and Wen (2011), in studies related to Botany, compared the performance of the growth of a tree species - Carya Cathayensis Sarg by PCA methods and Analytic Hierarchy Process (AHP), identifying the advantages and the disadvantages of each method, although

Mait, 2010), and ant colony (Goodarzi; Freitas; Jensen, 2009; Allegrini; Oliveri, 2011).

validation to determine the appropriate number of latent variables.

the results obtained by both have been essentially identical.

The first process in a refinery is atmospheric distillation or direct distillation, where components of crude oil are separated into different sections using different boiling points. The main products obtained in this process are: liquefied petroleum gas (LPG), naphtha precursor of gasoline, jet fuel, diesel and fuel oil.

Additionally, refineries usually have a second tower, vacuum distillation, to produce diesel cuts. These intermediate streams feeding a chemical process called Fluid Catalytic Cracking (FCC). In this, two noble streams are generated: LPG, and gasoline. It is a refining scheme much more flexible, but though modern, may also present difficulties for framing products stricter specifications.

The production scheme level 3 is more flexible and cost effective than the previous one, because it uses the chemical process of Coking, which transforms a fraction of lower value vacuum residue of distillation towers, in the noblest products like LPG, gasoline, naphtha and diesel oil.

This final refining scheme incorporates the process Hydrotreating of middle fractions generated in the Coker Unit, enabling increased supply of diesel with good quality. This scheme allows a more balanced supply of gasoline and diesel oil, producing more diesel and less gasoline than the previous settings.

Of course, there are other macro-processes and auxiliary processes such as water treatment plant, effluent disposal, sulfur recovery units, units of hydrogen generation and consequently other interconnections, details of which are not subject of this work (ANP, 2012).
