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Controlling the State of Machine Tools

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Russian Engineering Research Aims and scope

Abstract

Globally, manufacturers make great efforts to maintain the performance of industrial equipment. Developers and researchers are interested in automated approaches to maintaining the performance of equipment, especially at enterprises with high degrees of computerization and comprehensive information systems. In the present work, a new approach is outlined: an autonomous control system for maintaining the condition of metal-cutting machines. This approach is based on prior work in the field and permits maintenance on the basis of autonomous control of the state of machine tools. The structure of a system with the following generalized control functions is presented: decision making; and the issuing of commands on the basis of built-in resources. The formulation of control decisions employs the theory of fuzzy sets and fuzzy logic. By means of the ANFIS fuzzy network system, the autonomy of state control of the machine tool may be assessed. Criticality assessment of the condition of machine tools and their components is important in making decisions as to the setup of systems controlling the condition of equipment at enterprises, with assessment of their efficiency. In the monitoring subsystem, provision is made for assessment of the diagnostic results, prediction, and the generation of control decisions so as to prevent disruptions of machine-tool operation.

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Authors and Affiliations

  1. Don State Technical University, Rostov-on-Don, Russia

    A. K. Tugengol’d, V. P. Dimitrov, L. V. Borisova & M. Yu. Solomykin

  2. Rostov Research Institute of Radio and Communications, Rostov-on-Don, Russia

    R. N. Voloshin

Authors
  1. A. K. Tugengol’d
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  2. V. P. Dimitrov
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  3. L. V. Borisova
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  4. R. N. Voloshin
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  5. M. Yu. Solomykin
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Corresponding authors

Correspondence to A. K. Tugengol’d, V. P. Dimitrov, L. V. Borisova, R. N. Voloshin or M. Yu. Solomykin.

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Translated by Bernard Gilbert

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Tugengol’d, A.K., Dimitrov, V.P., Borisova, L.V. et al. Controlling the State of Machine Tools. Russ. Engin. Res. 38, 1056–1062 (2018). https://doi.org/10.3103/S1068798X18120304

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  • DOI: https://doi.org/10.3103/S1068798X18120304

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