Integration of batching and scheduling for hot rolling production in the steel industry

2007 ◽  
Vol 36 (5-6) ◽  
pp. 431-441 ◽  
Author(s):  
Xianpeng Wang ◽  
Lixin Tang
2012 ◽  
Vol 157-158 ◽  
pp. 719-726
Author(s):  
Hai Xiong Wang ◽  
Ji Bin Li ◽  
Hai Jun Liu ◽  
Chang Sheng Wang

In order to carry out automatic transformation to the two-roll reversible hot-rolling mill of a aluminum plate production factory, firstly a series of mathematical models of aluminum plate hot-rolling parameters are established, then a new optimization algorithm which is suitable for aluminum plate rolling production combined with the various constraints in the rolling process is proposed, and rolling schedule optimization software system is developed. Finally, by measuring the process parameters in rolling production site and applying the optimized rolling schedule to the rolling production, many test data are obtained. The analysis of test results and evaluation of the practical production show that the mathematical models established have high accuracy compared with the old rolling schedule. The optimization schedule can not only ensure the production quality, but also has higher efficiency and less energy consumption.


2010 ◽  
Vol 36 (2) ◽  
pp. 282-288 ◽  
Author(s):  
Chun-Yue YU ◽  
Cheng-En WANG ◽  
Rong-Xia QU

2011 ◽  
Vol 88-89 ◽  
pp. 307-313
Author(s):  
Ye Jian Yang ◽  
Ze Yi Jiang ◽  
Xin Xin Zhang

According to the technical demand of hot-rolling production in steel plant, a production scheduling mathematical model was proposed with the aim of reducing the production cost and optimizing the product quality. The scheduling of reheating furnaces which was summed up as the Boolean satisfiability problem was involved in rolling scheduling optimization which was summed up as the multiple traveling salesman problem with uncertain traveling salesman number, and a two-stage genetic-tabu algorithm was designed to solve the problem. It was shown that, the model could fully meet the demand of hot-rolling production. Compared to the human-computer method, the results had better performance on high production and energy efficiency.


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