A two-stage intelligent optimization system for the raw slurry preparing process of alumina sintering production

Authors:
Chunhua Yang;Weihua Gui;Lingshuang Kong;Yalin Wang
Affiliations:
School of Information Science and Engineering, Central South University, Changsha 410083, China;School of Information Science and Engineering, Central South University, Changsha 410083, China;School of Information Science and Engineering, Central South University, Changsha 410083, China and College of Communication and Electric Engineering, Hunan University of Arts and Science, Changde ...;School of Information Science and Engineering, Central South University, Changsha 410083, China
Venue:
Engineering Applications of Artificial Intelligence
Year:
2009

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Abstract

The raw slurry preparing is a key process to guarantee product for alumina sintering production. To obtain the qualified raw slurry in the presence of uncertainty, a two-stage intelligent optimization system, which weakens uncertainty effects through optimization of raw material proportioning and re-mixing operation, is developed. At the first stage, an integrated model combining the first principle with neural networks is built to predict the raw slurry quality, and a multi-objective hierarchical expert reasoning strategy is proposed to determine an optimal set point of raw slurry proportioning. At the second stage, an optimal scheduling model with uncertainty is built to provide an optimal combination of selected tanks for the mixing of raw slurry in full-filled tanks. The practical running results show that the eligibility rate of raw slurry is effectively improved, and the raw slurry preparing process is successfully simplified and the energy consumption is also obviously reduced.