Title :
Research on energy consumption analysis of beer brewing process
Author :
Jing Bai ; Tiecheng Pu ; Jisheng Xing ; Guocheng Niu ; Shuran Zhang ; Qiang Liu
Author_Institution :
Coll. of Electr. & Inf. Eng., Beihua Univ., Jilin, China
Abstract :
Because there are many coterminous workshop sections in beer brewing process and the reaction mechanism is very complex, it is difficult to analyze the energy consumption. Aiming at the problem, the analysis method of energy consumption is proposed based on the production data. First, energy consumption of beer brewing process is analyzed using the data envelopment analysis (DEA). The relative efficient productive batches are obtained. Secondly, the less dimensional production data are obtained using the principal component analysis (PCA) which depresses the correlation among the variables. Finally, the energy consumption of brewing process is modeled using radial basis function neural network (RBFNN), and the energy consumption model with the minimum error is also built by adjusting the width of the radial basis function. The simulation result shows that the model can be used to analyze and predict the energy consumption of the beer brewing process effectively.
Keywords :
beverages; data envelopment analysis; energy consumption; fermentation; principal component analysis; production engineering computing; radial basis function networks; DEA; PCA; RBFNN; beer brewing process; data envelopment analysis; energy consumption analysis; principal component analysis; productive batches; radial basis function neural network; Analytical models; Biological neural networks; Conferences; Data models; Energy consumption; Principal component analysis; Production; data envelopment analysis; neural network; principal component analysis;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6022892