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Newly Elaborated Hybrid Algorithm for Optimization of Robot Arm’s Trajectory in Order to Increase Efficiency and Provide Sustainability in Production

Author

Listed:
  • Rabab Benotsmane

    (Department of Information Technology, University of Miskolc, 3515 Miskolc, Hungary)

  • László Dudás

    (Department of Information Technology, University of Miskolc, 3515 Miskolc, Hungary)

  • György Kovács

    (Institute of Logistics, University of Miskolc, 3515 Miskolc, Hungary)

Abstract

Nowadays, resources for production (raw materials, human, energy, etc.) are limited, while population, consumption and environmental damage are continuously increasing. Consequently, the current practices of resource usage are not sustainable. Therefore, manufacturing companies have to change to environmentally friendly and innovative technologies and tools, e.g., industrial robots. Robots are necessary in the production sector and also in terms of sustainability: (1) the application of robots is needed to compensate for the lack of human resources; (2) robots can increase productivity significantly; and (3) there are several hazardous (e.g., chemical, physical) industrial tasks for which robots are more adequate than human workforce. This article introduces a newly elaborated Hybrid Algorithm for optimization of a robot arm’s trajectory by the selection of that trajectory that has the smallest cycle time. This Hybrid Algorithm is based on the Tabu Search Algorithm and also uses two added methods—Point Insertion and Grid Refinement—simultaneously to find more precisely the optimal motion path of the robot arm in order to further reduce the cycle time and utilize the joints’ torque more efficiently. This Hybrid Algorithm is even more effective than applying the Tabu Search method alone and results in even higher efficiency improvement. The Hybrid Algorithm is executed using MATLAB software by creating a dynamic model of a 5 degree-of-freedom robot arm. The main contribution of the research is the elaboration of the new Hybrid Algorithm, which results in the minimization of robot arms’ motion cycle times, causing a significant increase in productivity and thus a reduction in specific production cost; furthermore, obstacles in the workspace can be avoided. The efficiency of the Hybrid Algorithm is validated by a case study showing that application of the new algorithm resulted in 32% shorter motion cycle time.

Suggested Citation

  • Rabab Benotsmane & László Dudás & György Kovács, 2021. "Newly Elaborated Hybrid Algorithm for Optimization of Robot Arm’s Trajectory in Order to Increase Efficiency and Provide Sustainability in Production," Sustainability, MDPI, vol. 13(15), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8193-:d:599106
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    References listed on IDEAS

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    Cited by:

    1. Huihui Shi & Qiang Chen, 2022. "Error-Tracking Iterative Learning Control for the Constrained Flexible-Joint Manipulator with Initial Errors," Sustainability, MDPI, vol. 14(19), pages 1-21, September.
    2. Rabab Benotsmane & György Kovács, 2023. "Optimization of Energy Consumption of Industrial Robots Using Classical PID and MPC Controllers," Energies, MDPI, vol. 16(8), pages 1-28, April.

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