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Publikācija: Energy Efficient Use of Multirobot Production Lines in the Automotive Industry: Detailed System Modeling and Optimization

Publication Type Scientific article indexed in SCOPUS or WOS database
Funding for basic activity Unknown
Defending: ,
Publication language English (en)
Title in original language Energy Efficient Use of Multirobot Production Lines in the Automotive Industry: Detailed System Modeling and Optimization
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Authors Dāvis Meike
Marcello Pellicciari
Giovanni Berselli
Keywords Energy Efficient Robotics, Trajectory Planning, Robotic Manufacturing, Virtual Prototyping
Abstract This paper quantitatively reports about potential energy savings on robotic assembly lines for the automotive industry. At first, a detailed system model is described, which improves previously published results by explicitly considering both manipulator and electrical drive dynamics. The model closely captures experimental data in terms of actuation torques and servodrive voltages, which are directly used to derive the plant input power. Then, two practical methods for reducing the overall energy consumption are evaluated. The methods rely on: 1) implementation of energy-optimal trajectories, obtained by means of time scaling, concerning the robots’ motion from the last process point to the home positions; 2) reduction of the energy consumption via earlier release of the actuator brake when the robots are kept stationary. Simulation results, based on the production timing characteristics measured on a real plant, clearly shows that the system energy consumption can be effectively reduced without negative effects on the production rate.
DOI: 10.1109/TASE.2013.2285813
Hyperlink: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6668986 
Reference Meike, D., Pellicciari, M., Berselli, G. Energy Efficient Use of Multirobot Production Lines in the Automotive Industry: Detailed System Modeling and Optimization. IEEE Transactions on Automation Science and Engineering (T-ASE), 2013, Vol.11, Iss.3, pp.798-809. ISSN 1545-5955. Available from: doi:10.1109/TASE.2013.2285813
Additional information Citation count:
ID 16165