Metallurgical Models for
Rolling Mill Level 2
Mill Metallurgical Model
for Level 2
In order to determine the retained strain and to estimate
the grain size, etc., microstructure modeling would be
performed pass by pass. The microstructure modeling may be
conducted for the following parameters or processes:
Static and dynamic recrystallization and grain growth,
as well as precipitation. Learning procedure could be designed
and optimized. In this aspect the semi-empirical model may
also be used.
Retained strain, as mentioned earlier. Theoretical and
semi-empirical approaches with microstructure simulation
would be particularly carried out. Empirical models
collected in the past could be evaluated and combined with the
Microstructure-affected flow stress. Studies
would also cover
the initial grain size effect and the prediction of the flow stress based on the
chemical composition, etc.
The hold and the resume pass.
Phenomenon involved in the hold and resume pass would be
further studied. Microstructure simulation and flow stress
modeling would be carried out for the hold period.
Microstructure evolution and finish steel properties
based on the given draft-schedule, to verify that various
requirements (shape, properties, etc.) are satisfied. Option
to use various algorithms (both linear and nonlinear ones)
could be provided.
Mill Level 2 Model Architecture
newly developed Level 2 model may include following modules
Rolling Process Models, to perform model calculations for, such as force, temperature, roll flattening, roll deflection, thermal crown, roll wear, steel deformation. It
should call the metallurgical modules to determine microstructure, retained strain and flow stress, etc.
Metallurgical Models, to determine retained strain, grain size, rolled steel properties, etc., by
integrating with intelligent learning such as neural network, fuzzy logic and expert system.
Expert System, which consists of logics, data and influence factors on the mechanical, thermal and metallurgical parameters depending on rolling and thermal processes. Past mill-experiences
could be programmed as a portion of the expert system.
System Learning, based on rolling process models, in which the neural network provides the correcting factors for the model coefficients, and fuzzy logic rules and expert system provide guidelines (upper and lower boundaries, etc.) for the learning.
Draft Scheduling, which is based on various requirements (shape, properties, etc.) and various algorithms, with special attention paid to nonlinear algorithms. Microstructure and finish properties will be predicted for every newly generated pass schedule.
Rolling Mill Level 2
Model primarily consists
rolling process models
Rolling mill force
Work List on Level 2 and Mill Modeling
Metal Pass Recent
Technical papers published
in the February and March of
publications are primarily
on Level 2, Level 2 model
and process automation.
Metal Pass has dozens of
research reports and some
available at no charge for the Metal Pass Consulting clients (under approval by
Dr. Benjamin Li).