Quality Prediction Modeling of Palm Oil Refining Plant in Malaysia Using Artificial Neural Network Models
-
2018-08-14 https://doi.org/10.14419/ijet.v7i3.26.17454
-
Artificial Neural Network, Edible Oil Refining, Palm Oil, Quality Prediction -
Abstract
Malaysia is currently one of the biggest producers and exporters of palm oil and palm oil products. In the growth of palm oil industry in Malaysia, quality of the refined oil is a major concern where off-specification products will be rejected thus causing a great loss in profit. In this paper, predictive modeling of refined palm oil quality in one palm oil refining plant in Malaysia is proposed for online quality monitoring purposes. The color of the crude oil, Free Fatty acid (FFA) content, bleaching earth dosage, citric acid dosage, activated carbon dosage, deodorizer pressure and deodorizer temperature were studied in this paper. The industrial palm oil refinery data were used as input and output to the Artificial Neural Network (ANN) model. Various trials were examined for training all three ANN models using number of nodes in the hidden layer varying from 10 to 25. All three models were trained and tested reasonably well to predict FFA content, red and yellow color quality of the refined palm oil efficiently with small error. Therefore, the models can be further implemented in palm oil refinery plant as online prediction system.
Â
Â
-
References
[1] Gibon, V., Greyt, D. W., and Kellens, M., “Palm oil refiningâ€, European Journal of Lipid Science and Technology, Vol 109(4), (2007), pp. 315-335.
[2] Silva, S. M., Sampaio, K. A., Ceriani, R., Verhé, R., Stevens, C. Greyt, W. D. and Meirelles, A. J. A., “Adsorption of carotenes and phosphorus from palm oil onto acid activated bleaching earth: Equilibrium, kinetics and thermodynamicsâ€, Journal of Food Engineering, Vol.118, (2013), pp. 341–349.
[3] Basiron, Y., Palm Oil, in: Shahidi, F. (Ed.), Bailey’s Industrial Oil and Fat Products, 6 ed. John Wiley & Sons, Inc., (2005), pp. 333 - 429.
[4] Hussin, F., Aroua, M. K. and Wan-Daud, W. M. A., “Textural characteristics, surface chemistry and activation of bleaching earth: A review.†Chemical Engineering Journal, Vol.170, (2011), pp. 90–106.
[5] Puah, C. W., Choo, Y. M., Ma, A. N., and Chuah, C. H., “Degumming and Bleaching: Effect on Selected Constituents of Palm Oilâ€, Journal of Oil Palm Research, Vol.16 (2), (2004), pp. 57-63.
[6] Skevin, D., Domijan, T., Kraljic, K., Kljusuric, J. G., Nederal, S. and Obranovic, M., “Optimization of Bleaching Parameters for Soybean Oilâ€, Food Technology Biotechnology, Vol.50 (2), (2012), pp. 199-207.
[7] Taylor D. R., “Bleachingâ€, John Wiley & Sons, Inc., (2005), pp.321-330
[8] Greyt W. D., and Kellens, M., “Deodorizationâ€, John Wiley & Sons, Inc., (2005), pp. 321-330.
[9] Almeida, J. S., “Predictive non-linear modeling of complex data by artificial neural networksâ€, Current Opinion in Biotechnology, Vol.13, (2002), pp. 72–76.
[10] Saxen, H. and Pettersson, F., “Method for the Selection of Inputs and Structure of Feedforward in Neural Networksâ€, Computer and Chemical Engineering, Vol.30, (2006), pp.1038-1047.
[11] Ahmad, A.L., Azid, I. A., Yusof, A.R., and Seetharamu, K.N., “Emission Control in Palm Oil Mills using Artificial Neural Network and Genetic Algorithmâ€, Computers & Chemical Engineering, Vol.28(12), (2004), pp. 2709-2715.
[12] Abdullah, S. and Eow C. T., “Prediction of Palm Oil Properties using Artificial Neural Networkâ€, International Journal of Computer Science and Network Security, Vol.8(8), (2008), pp. 101-106.
[13] Ismail, Z. and Khamis, A., “Neural Network in Modeling Malaysian Oil Palm Yieldâ€, American Journal of Applied Sciences Vol.8 (8), (2011), pp. 796-803.
[14] Sulaiman N. S. and Mohd-Yusof, K., “Artificial neural network-based model for quality estimation of refined palm oil,†2015 15th International Conference on Control, Automation and Systems (ICCAS), Busan, (2015), pp. 1324-1328.
[15] N. Tehlah, P. Kaewpradit, I.M. Mujtaba, “Artificial neural network based modeling and optimization of refined palm oil processâ€, Neurocomputing, Vol.216, (2016), pp. 489-501.
[16] Morad, N. A., Zin, R. M., Yusof, K. M., and Aziz, M. K. A., “Process Modelling of Combined Degumming and Bleaching in Palm Oil Refining Using Artificial Neural Networkâ€, JAOCS, Journal of the American Oil Chemists' Society, Vol.87(11), (2010), pp. 1381-1388.
[17] Abdul-Hadi N. and Che-Mat, C.R, “Prediction Model Based on Artificial Neural Network for Industrial Bleaching and Degumming Process of Crude Palm Oil†International Journal of Engineering and Innovative Technology (IJEIT), Vol.6 (1), (2016), pp. 32-38.
-
Downloads
-
How to Cite
Sulaiha Sulaiman, N., Mohd-Yusof, K., & Mohd-Saion, A. (2018). Quality Prediction Modeling of Palm Oil Refining Plant in Malaysia Using Artificial Neural Network Models. International Journal of Engineering & Technology, 7(3.26), 19-22. https://doi.org/10.14419/ijet.v7i3.26.17454Received date: 2018-08-14
Accepted date: 2018-08-14
Published date: 2018-08-14