Development of Optimization Method for Reheating Furnace Operation

Open Access
Kominami, Masahito
Graduate Program:
Industrial Engineering
Master of Science
Document Type:
Master Thesis
Date of Defense:
Committee Members:
  • Robert Carl Voigt, Thesis Advisor
  • Dynamic Programming
  • Optimization
  • Furnace control
  • Simulation
  • Heat transmission
  • Difference method
The cost of operating reheating furnaces, used for heating mainly billets or blooms in steel rolling mills is quite large. Therefore, reduction of reheating costs is one of the major challenges in rolling mills. The reheating furnaces are usually controlled manually by operators who must respond to changes in downstream rolling conditions. Their reheating furnace control is not consistent and has been observed to depend on operator characteristics, experiences or skills. In many cases, steel billet lots are small, requiring various types of billets/blooms with different specifications to be heated in a furnace at the same time. This means that it is hard to find the optimal heating conditions due to changes in product mix. Additionally, once operational troubles happen at downstream rolling operations, unexpected stoppages are caused. The operators of furnaces are then required to adjust reheating furnace temperatures so that billet/bloom overheating does not occur. It is also difficult to re-establish steady-state reheating condition after the stoppages, because the bulk temperature of the billets/blooms, can be quite different than the observed billet/bloom surface temperature. Therefore, the operators have to rely on their experience when making furnace adjustment during and after stoppages. In this research, a billet simulation model for a walking hearth type reheating furnace was created and an optimization method for economical operation is proposed. The simulation model employs a three dimensional (3-D) difference method and a dynamic programming methodology developed in Matlab. Also, the thermal radiation view factor from bricks inside furnaces to billets/blooms was calculated dynamically. The hearth temperature was approximated using the simulated bottom face temperature of billets. In the optimization method, the extraction temperatures of billets are predicted for current operating conditions. Based on the result, the furnace temperature in each zone of the furnace is controlled. The major feature of this control strategy is having two policies. One is targeting the zone and the time period where billets temperatures can be controlled effectively in changing furnace temperature set points, considering heating and cooling delay and updating the feasible region dynamically. The other is prioritizing the zones for increasing furnace temperature. It was first zone 3, then zone 2, then zone1 and finally zone 4, considering the differences in heat transmission efficiency. The final goal of this thesis is to develop an optimization method that can find an optimal solution for furnace temperature control within 10 [min]. This goal was achieved by developing a 2-D billet temperature simulation model, selecting appropriate time increments and mesh size, setting amplifier and lower limiter for temperature increments in optimization, and selective billet tracking for optimization for billet temperature increments.