控制(管理)
材料科学
生产(经济)
质量(理念)
玻璃生产
工艺工程
计算机科学
工程类
复合材料
人工智能
物理
经济
宏观经济学
量子力学
作者
H.P.H. Muijsenberg,Glenn Neff,Josef Müller,Josef Chmelař,Robert F. Bodi,F. Matustikj
出处
期刊:Ceramic engineering and science proceedings
日期:2008-03-26
卷期号:: 33-45
被引量:4
标识
DOI:10.1002/9780470291306.ch3
摘要
ABSTRACT Energy prices keep increasing, so glass producers are looking for any solution improving energy efficiency of the glass making. At the same moment glass producers are convinced about the advantages of advanced control systems. It has been verified on many plants that such control type makes a glass melting process more consistent and stable. Its implementation gives to the glass producers a competitive advantage on the glass production field. The benefits are known to most glass producers. To stay a leader these days it is necessary to add something more to the process. The main accent lies in looking for complex problem solutions related to the process control - how to produce as cheap as possible (eg improve energy efficiency) while the high-quality glass production is preserved, how to minimize time for thejob changes, etc. At present, when the glass production needs to produce products of consistent excellent glass quality at high yield and low energy usage, it is almost impossible to control the production manually. Therefore a group of advanced control techniques was developed for an automatic control. One of commonly used is Model (based) Predictive Control (MPC). Correct using of MPC together with knowledge of glass production results in process stabilization, increasing glass quality and energy savings. Glass Service has developed the software package Expert System ES-Ill entirely determined for the control of a glass production process. It utilizes all advantages of MPC system plus a combination of Fuzzy control and Neural Networks. Some of these advanced techniques used in ES-Ill for glass production optimal control are described in this paper. Recent development targets use of the CFD (Computer Flow Dynamics) of the glass furnace as part of the control strategy using GS Glass Furnace Model (GS GFM).
科研通智能强力驱动
Strongly Powered by AbleSci AI