Application of Decision Support Expert Systems for Improved gasoline yield in Refinery Catalytic Cracking

• Published in: Procedia computer science 2024, Vol.232, p.3044-3053
• Main Authors: Oyejide, O.J., Faiz, A., Muhammad, A., Okwu, M.O.
• Format: Article
• Language: English
• Subjects: Catalytic Cracking (CC) unit; Factor loadings; Kendall Coefficient of concordance (KCC); Principal Component Analysis (PCA)
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2024.02.120

The Catalytic Cracking Unit (CCU) stands out as the primary factor responsible for enhancing gasoline production in the refinery. This paper provides a deep insight on the complexity of the factors within this unit, explore their broader implications, and offer a rationale for their technical significance. A survey approach involving the use of Principal Component Analysis (PCA) facilitated by StatistiXL software package and Kendall Coefficient of Concordance (KCC) to measure agreement among the respondents was employed. A total of 32 variables were identified, and questionnaires were developed using Rensis Likert's 5-point scale. These questionnaires were then administered to 100 respondents. Prior to this step, the Kendall Coefficient of Concordance was utilized to establish the sequential order of importance among these identified factors. The results obtained showed an index of agreement among the judges in ranking the variables W, as 0.54, the null hypothesis of disconcordance among the judges was rejected at a p-value of 0.01. The study identified 14 significant variables based on the KCC results, including Catalytic Cracking Charge, Mid Riser Temperature, Riser Inlet Temperature, Riser Outlet Temperature, and Stripper Level. Additionally, Principal Component Analysis (PCA) effectively condensed the set of 32 variables into four manageable clusters. The integration of data analytics techniques, such as KCC and PCA, alongside expert opinions and collected data enabled the assessment of the influence of independent variables on gasoline yield and the categorization of these variables. This study offers valuable insights for both academia and the industry, especially in the context of the Catalytic Cracking Unit.