Anton Slesarev , Yandex, “Unmanned cars technology”
Gleb Gusev, Yandex, “Natural Language Processing”
Vitaly Shiryaev, NLMK, “Data analysis and mathematical modeling on NLMK”
The lecture will briefly outline the scope of production problems successfully solved at Novolipetsk Steel that are associated with the implementation of machine learning, mathematical modelling and optimization algorithms. The primary focus will be on the two following problems – Optimization of the Thermal Power Station (TPS) Performance and the Prediction of the Work Rolls Wear in the Hot Strip Mill.
The first problem is associated with the reduction of the natural gas procurement that is used for the electricity generation and steam production. This problem is addressed by achieving the optimal load on the TPS boilers and the maximum utilization of the coke and blast furnace gases, which are the byproducts of the metallurgical processes at NLMK. The optimal load takes into account that the boilers efficiency depends on the utilized gases proportion, as well as on their pressure and other factors. The dependence of vapor production on natural gas consumption by each boiler is found from the historical data by using advanced statistical methods.
As for the second problem focused on the work roll wear in the hot strip mill, the participants of the Summer School are invited to solve it during the extramural two-day competition. The competition results will be announced on the last day of the Summer School.
Tinkoff, “Artificial intelligence in financial analytics”
iPavlov, “Conversational AI”
Tutorials and workshops
Roni Stern, BGU of Negev, “Path planning”
Dmitry Yudin, MIPT, “Using CST to build a Cognitive Architecture controlling an NPC in a Computer Game”
We provide a step-by-step demonstration illustrating the main foundations of the CST Cognitive Systems Toolkit in building a cognitive architecture to work as an artificial mind for controlling an NPC (non-player character) in a 3D virtual environment computer game. We start by introducing the main foundations of CST: Codelets and Memories, and how they should be used to integrate a cognitive architecture, controlling the NPC. The demonstration is a hands-on programming activity, using Java and Netbeans as language/tool.
NLMK, “The prediction of rolls wear in the hot strip mill”
Prerequisites: Python, Anaconda (sklearn), Excel
Abstract. The metal processing in the hot strip mill is divided into the series of so-called rolling batches. After finishing each batch, the mill stops and the worn work rolls are replaced with the new ones. The removed rolls are then polished on the grinding machine in order to remove the surface defects and restore their original geometrical profile. After that, the rolls are installed back into the hot strip mill during its next stop.
The work rolls are utilized until their work surface, which is typically several centimeters thick, fully wears out. The wear is defined as the reduction of the roll diameter during its operation and the subsequent polishing. The wear depends on multiple factors such as the roll’s material, the roll’s position in the mill and the processed steel grade. The task is to create the mathematical model of the work roll wear by using the provided statistical data, as well as some physical reasoning. The model should be then used to predict the roll wear after processing each rolling batch.