CONTRIBUTION TO IMPROVING OF MACHINE PARTS MECHANICAL PROPERTIES BY THERMOMECHANICAL HARDENING

  • 1Institute of Mechanics of Udmurt Federal Research Center of the Ural Branch of the RAS, Izhevsk
  • 2University of Zilina, Faculty of Mechanical Engineering, Zilina, SK
  • 3Institute of Mechanics of Udmurt Federal Research Center of the Ural Branch of the RAS
  • 4Kalashnikov Izhevsk State Technical University, Izhevsk

Abstract

Current industrial production is characterized by requirements for improving the physical and mechanical properties of the used material. This causes a workload creating a rather complex load on all types of machines and mechanisms during operation. The design of such objects is currently based on a wide range of computational and experimental methods that allow modelling their state and behaviour even in the case of complicated non-stationary loading conditions. In this paper, the authors focus on the statistical evaluation of selected manufacturing operations related to mechanical and thermomechanical processing of products [Kuric 2011]. For example, in the case of long pipe billets with a thickness coefficient of 2-4, practically the only way of their production in the metallurgical cycle is cross-roll piercing followed by reduction. This process has high productivity but at the same time certain disadvantages. These disadvantages limit the efficiency and the range of use of the pipe blanks obtained by piercing, which leads to a consequent shortening of the machine production cycle. The presented approaches allow changing the structure of technological processes of production of axisymmetric metal products, by modifying the thermomechanical processing at the beginning of the production cycle.

Recommended articles

DEVELOPMENT AND SIMULATION OF SPIKE NEURAL NETWORK ARCHITECTURE

MILAN SAGA, ALEXANDER I. KORSHUNOV, VICTOR YU. TRUBITSIN, TATYANA E. SHLYAHTINA, ZUZANA SAGOVA, KONSTANTIN A. SHLYAHTIN
Keywords: spiking neural network | Simulation | neuron | axon | dendrite | neurotransmitters