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Optimizing Energy Consumption of Industrial Robots with Model-Based Layout Design

Author

Listed:
  • Silviu Răileanu

    (Department of Automation and Applied Informatics, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Theodor Borangiu

    (Department of Automation and Applied Informatics, University Politehnica of Bucharest, 060042 Bucharest, Romania
    Academy of Romanian Scientists, 050094 Bucharest, Romania)

  • Ionuț Lențoiu

    (Department of Automation and Applied Informatics, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Mihnea Constantinescu

    (Department of Automation and Applied Informatics, University Politehnica of Bucharest, 060042 Bucharest, Romania)

Abstract

The paper describes the development of an optimization model for the layout of an industrial robot relative to known locations of served machines and operations to be performed. Robotized material handling applications, defined by trajectories (paths, speed profiles) and final points, are considered in this research. An energy-monitoring framework set up by joint velocities provides input data that are fed to the optimization model. The physical placement of the robot base stands for the decisional variables, while the objective function is represented by the total distance covered by individual joints along established task routes transposed into energy consumption. The values of the decisional variables are restricted by trajectory constraints (waypoints on paths), joint operating values and link dimensions. Modelling technique and practical results using the Microsoft Solver optimization tool from Excel for Microsoft 365, Version 2312 are reported for SCARA-type robots. The performance of the optimization model is compared with actual measurements of consumed energy on an Adept Cobra S600 SCARA robot.

Suggested Citation

  • Silviu Răileanu & Theodor Borangiu & Ionuț Lențoiu & Mihnea Constantinescu, 2024. "Optimizing Energy Consumption of Industrial Robots with Model-Based Layout Design," Sustainability, MDPI, vol. 16(3), pages 1-20, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:3:p:1053-:d:1326617
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    References listed on IDEAS

    as
    1. Toru Yamamoto & Hirofumi Hayama & Takao Hayashi & Taro Mori, 2020. "Automatic Energy-Saving Operations System Using Robotic Process Automation," Energies, MDPI, vol. 13(9), pages 1-14, May.
    2. Zhao, G.Y. & Liu, Z.Y. & He, Y. & Cao, H.J. & Guo, Y.B., 2017. "Energy consumption in machining: Classification, prediction, and reduction strategy," Energy, Elsevier, vol. 133(C), pages 142-157.
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