Statistical modeling for energy consumption and anomaly detection in rubber vulcanization process

Hai Dong Yang, Guo Sheng Liu, George Q. Huang, Xin Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)65-71
Number of pages7
JournalJournal of Energy Engineering
Issue number2
Publication statusPublished - Jun 2013
Externally publishedYes


  • Anomaly detection
  • Energy flow ratio
  • Energy-efficient management
  • Multivariate regression
  • Vulcanization process

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Energy Engineering and Power Technology
  • Waste Management and Disposal


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