Technical Papers
Aug 24, 2012

Statistical Modeling for Energy Consumption and Anomaly Detection in Rubber Vulcanization Process

Publication: Journal of Energy Engineering
Volume 139, Issue 2

Abstract

Factories are forced to pay for higher energy costs in the next decades because of increasing demand for energy and limited fuel resources. Efficient management of energy is among the greatest of challenges, especially for those energy-intensive manufacturing businesses. Research efforts have been continuously made to improve the efficiency in energy consumption, and methods and tools for energy efficiency management have been developed with respect to economics/cost and environment. This paper proposes a new energy-efficient management model by investigating energy consumption at tire manufacturing workstations. The model is then used to support efficacy and safety for manufacturing operations from the perspective of energy consumption. The proposed model is based on the statistical analysis of energy consumption in the rubber vulcanization process. The efficient energy usage is characterized by the ratio of energy flow into product manufacturing process. The energy flow ratio provides a quantitative measure for detecting system anomaly. A study case for tire vulcanization is presented to validate the proposed approach.

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Acknowledgments

The authors would like to thank the information management group of H factory for providing the experimental data and convenience of accessing the database system. The authors also would like to thank the anonymous reviewers for their useful suggestions. This work was supported by the National Natural Science Foundation of China (Grant No: 60973132), the Production-Education-Research Project of Guangdong Province and Ministry of Education (Grant No: 2011A090200050), and the Special Development Foundation of Modern Information Service of Guangdong Province (Grant No: GDEID2010IS035).

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Information

Published In

Go to Journal of Energy Engineering
Journal of Energy Engineering
Volume 139Issue 2June 2013
Pages: 65 - 71

History

Received: Oct 4, 2011
Accepted: Aug 16, 2012
Published online: Aug 24, 2012
Published in print: Jun 1, 2013

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Authors

Affiliations

Hai-Dong Yang [email protected]
Dept. of Mechatronics Engineering, Guangdong Univ. of Technology, 100 Waihuan Xi Rd., Guangzhou 510006, China. E-mail: [email protected]
Guo-Sheng Liu [email protected]
Dept. of Information Management Engineering, Guangdong Univ. of Technology (Longdong Campus), 161 Yinglong Rd., Guangzhou 510520, China (corresponding author). E-mail: [email protected]
George Q. Huang [email protected]
Dept. of Industrial and Manufacturing Systems Engineering, Univ. of Hong Kong, Pokfulam 999077, China. E-mail: [email protected]
Dept. of Mechatronics Engineering, Guangdong Univ. of Technology, 100 Waihuan Xi Rd., Guangzhou 510006, China. E-mail: [email protected]

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