The quality of steel strip produced in a wide strip rolling mill depends heavily on the careful selection of initial ground work roll profiles for each of the mill stands in the finishing train. In the past, these profiles were determined by human experts, based on their knowledge and experience. In this research, a Self-Organising Migration Algorithm (SOMA), a heuristic optimisation algorithm,...

J. Jaworski, T. Trzepieciński: Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, Rzeszów, Poland This paper presents the results of research on the determination of the coefficient of thermal conductivity and hot hardness of cutters made of selected grades of low-alloy high-speed steels, HS 6-5-2 and HS3-1-2. The investigations of hot hardness and yield stress...

M. Stańczyk, T. Figlus, The Silesian University of Technology, Faculty of Transport Katowice, Poland In the work the influence results of two different hardening coolant agents on the basic mechanical proprieties and microstructure of the round hot rolled bars were presented. The bars of 42CrMo4 steel were exposed to analysis, and for those bars in the hardening process, water and modern pro-ec...

The Self-Organizing Map (SOM) is one of the most popular neural network methods. It is a powerful tool in visualization and analysis of high-dimensional data in various engineering applications. The SOM maps the data on a two-dimensional grid which may be used as a base for various kinds of visual approaches for clustering, correlation and novelty detection. In this chapter, we present novel me...

The finishing train of a hot strip mill has been modelled by using a constant volume element model. The accuracy of the model has been increased by using an Artificial Neural Network (ANN). A non-linear Rank Based Genetic Algorithm has been developed for the optimization of the work roll profiles in the finishing stands of the simulated hot strip mill. It has been compared with eight other expe...