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Robotic Technological Processes Optimization in the Context of Digital Transformation of Industry

In: The Future of Industry

Author

Listed:
  • Markel Melnichenko

    (Komsomolsk-on-Amur State University)

  • Mikhail Gorkavyy

    (Komsomolsk-on-Amur State University)

  • Yuri Ivanov

    (Komsomolsk-on-Amur State University)

  • Aleksandr Gorkavyy

    (Komsomolsk-on-Amur State University)

Abstract

Modern industrial enterprises equipped with robotic production complexes rely on highly efficient models of technological processes, including energy consumption, to reduce production costs. The paper presents a method for enhancing the energy efficiency of robotic technological processes characterized by a limited class of complexes of movement trajectories, using the optimization algorithms developed by the authors. The presented studies were based on methods of identification, analysis and synthesis, as well as mathematical, in particular, simulation modeling to create models of energy consumption of robotic technological complexes. Automation of the proposed solutions was carried out using intelligent tools in the MATLAB environment. The study investigates robotic technological processes for laying blocks and mechanical processing, identifies the parameters of the processes under consideration, and develops reduced models of energy consumption of industrial robots as part of robotic technological complexes. We present algorithms for optimizing trajectory movements for processes with a predominance of long-stroke movements (cargo stowage) and with a predominance of short-stroke movements (mechanical processing) according to the criteria of minimizing energy consumption and time for performing a technological operation. The paper delivers the results of testing the proposed optimization solutions and the calculation of energy benefits from implementation in production.

Suggested Citation

  • Markel Melnichenko & Mikhail Gorkavyy & Yuri Ivanov & Aleksandr Gorkavyy, 2024. "Robotic Technological Processes Optimization in the Context of Digital Transformation of Industry," Lecture Notes in Information Systems and Organization, in: Andrea Appolloni & Vikas Kumar & Evgeny Kuzmin & Victoria Akberdina (ed.), The Future of Industry, pages 249-269, Springer.
  • Handle: RePEc:spr:lnichp:978-3-031-66801-2_17
    DOI: 10.1007/978-3-031-66801-2_17
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