Autors: Kostov, B. V., Hristov, V. D.
Title: Optimizing Cycle Time of Industrial Robot for Loading Molding Machine: A Comprehensive Analysis and Optimization Approach
Keywords: accuracy; industrial robots; optimizing; path planning; pneu

Abstract: In the highly competitive manufacturing industry, optimizing the cycle time of industrial robots plays a crucial role in enhancing production efficiency and maximizing profitability. This paper presents a comprehensive analysis and optimization approach for reducing the cycle time of industrial robots specifically used for loading molding machines. The study begins by investigating the key factors that affect the cycle time, including robot movement, tool selection, part handling, and machine setup. Through in-depth analysis and empirical data collection, the paper identifies the critical bottlenecks and inefficiencies that contribute to prolonged cycle times. Based on the identified issues, a systematic optimization approach is proposed to streamline the robot loading process. This approach encompasses various strategies, such as optimizing robot trajectories, implementing intelligent part recognition systems, improving gripper designs, and leveraging advanced machine learning alg.

References

    Issue

    5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2023, 2023, Turkey, DOI 10.1109/HORA58378.2023.10156771

    Цитирания (Citation/s):
    1. Roman Voliansky, Oleksiy Statsenko, Oleg Sergienko, Mykola Zhelinskyi, Oleksandr Sadovoi, Nina Volianska, "Optimal Controller Design for Plants with Polynomial Nonlinearities", 2023 IEEE 7th International Conference on Methods and Systems of Navigation and Motion Control (MSNMC), pp.60-65, 2023. - 2023 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus