This paper presents a new method for optimizing the layout position of several Industrial Robots (IRs) placed within manufacturing work-cells, in order to execute a set of specified tasks with the minimum energy consumption. At first, a mechatronic model of an anthropomorphous IR is developed, by leveraging on the Modelica/Dymola built-in capabilities. The IR sub-system components (namely mechanical structure, actuators, power electronic and control logics) are modeled with the level of detail strictly necessary for an accurate prediction of the system power consumption, while assuring efficient computational efforts. Secondly, once each IR task is assigned, the optimal work-cell layout is computed by using proper optimization techniques, which numerically retrieve the IR base position corresponding to the minimum energy consumption. As an output to this second development stage, a set of color/contour maps is provided, that depicts both energy demand and time required for the task completion as function of the robot position in the cell to support the designer in the development of an energy-efficient layout. At last, two robotic manufacturing work-cells are set-up within the Delmia Robotics environment, in order to provide a benchmark case study for the evaluation of any energy saving potential. Numerical results confirm possible savings up to 20% with respect to state-of-the-art work-cell design practice.
Energy-optimal layout design of robotic work cells: Potential assessment on an industrial case study
BERSELLI, GIOVANNI;
2017-01-01
Abstract
This paper presents a new method for optimizing the layout position of several Industrial Robots (IRs) placed within manufacturing work-cells, in order to execute a set of specified tasks with the minimum energy consumption. At first, a mechatronic model of an anthropomorphous IR is developed, by leveraging on the Modelica/Dymola built-in capabilities. The IR sub-system components (namely mechanical structure, actuators, power electronic and control logics) are modeled with the level of detail strictly necessary for an accurate prediction of the system power consumption, while assuring efficient computational efforts. Secondly, once each IR task is assigned, the optimal work-cell layout is computed by using proper optimization techniques, which numerically retrieve the IR base position corresponding to the minimum energy consumption. As an output to this second development stage, a set of color/contour maps is provided, that depicts both energy demand and time required for the task completion as function of the robot position in the cell to support the designer in the development of an energy-efficient layout. At last, two robotic manufacturing work-cells are set-up within the Delmia Robotics environment, in order to provide a benchmark case study for the evaluation of any energy saving potential. Numerical results confirm possible savings up to 20% with respect to state-of-the-art work-cell design practice.File | Dimensione | Formato | |
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