Paper Title:
Process Optimization of Candy Production Based on Data Mining
  Abstract

There are complicated correlations between process parameters and quality indicators in candy manufacturing. The objective of this work is to develop an optimization system of candy production process to improve final candy quality and to increase production efficiency. The study is conducted by using an artificial neural network data mining method to obtain optimization knowledge of process parameters from large amount of saved process data. The software platform including data processing, statistic analysis, data mining and graphical display module was developed and the quality forecasting models for typical processing operations were discussed. Experiments indicated that the system can optimize and predict the quality of candy production process effectively.

  Info
Periodical
Advanced Materials Research (Volumes 282-283)
Chapter
Chapter 4: Intelligent Materials, Photonics and Power
Edited by
Helen Zhang and David Jin
Pages
662-665
DOI
10.4028/www.scientific.net/AMR.282-283.662
Citation
J. L. Zhang, J. G. Yang, S. G. Shen, H. Y. Chen, "Process Optimization of Candy Production Based on Data Mining", Advanced Materials Research, Vols. 282-283, pp. 662-665, 2011
Online since
July 2011
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Price
$32.00
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