| 1. |
|
|
| 2. |
- Pellicciari, M., et al.
(författare)
-
Object-oriented modeling of industrial manipulators with application to energy optimal trajectory scaling
- 2011
-
Ingår i: ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011; Washington, DC; United States; 28 August 2011 through 31 August 2011. - 9780791854822 ; 5:A and B, s. 997-1006
-
Konferensbidrag (refereegranskat)abstract
- The development of safe, energy efficient mechatronic systems is currently changing standard paradigms in the design and control of industrial manipulators. In particular, most optimization strategies require the improvement or the substitution of different system components. On the other hand, from an industry point of view, it would be desirable to develop energy saving methods applicable also to established manufacturing systems being liable of small possibilities for adjustments. Within this scenario, an engineering method is reported for optimizing the energy consumption of serial manipulators for a given operation. An object-oriented modeling technique, based on bond graph, is used to derive the robot electromechanical dynamics. The system power flow is then highlighted and parameterized as a function of the total execution times. Finally, a case study is reported show- ing the possibility to reduce the operation energy consumption when allowed by scheduling or manufacturing constraints.
|
|
| 3. |
- Vergnano, Alberto, et al.
(författare)
-
Embedding detailed robot energy optimization into high-level scheduling
- 2010
-
Ingår i: 2010 IEEE International Conference on Automation Science and Engineering, CASE 2010. - 9781424454471 ; , s. 386-392
-
Konferensbidrag (refereegranskat)abstract
- Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modelled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system is presented. It shows that there exists a possibility for a significant reduction of the energy consumption, in comparison to state-of-the-art scheduling approaches. © 2010 IEEE.
|
|
| 4. |
- Vergnano, Alberto, et al.
(författare)
-
Modeling and Optimization of Energy Consumption in Cooperative Multi-Robot Systems
- 2012
-
Ingår i: IEEE Transactions on Automation Science and Engineering. - 1558-3783 .- 1545-5955. ; 9:2, s. 423-428
-
Tidskriftsartikel (refereegranskat)abstract
- Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modeled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system and an experiment on an industrial robot are presented. They show that there exists a real possibility for a significant reduction of the energy consumption in comparison to state-of-the-art scheduling approaches. Note to Practitioners-The motivation for this work is the great interest of companies on energy consumption optimization, looking for cost reduction and sustainability in manufacturing. Existing optimization methods focus on different levels of details. A high-level model would be able to optimize the overall system. Unfortunately, due to the high computational cost, it can hardly consider the deep level of mechanical and electrical parameters, which determine the real energy consumption. This paper presents a novel method to embed detailed energy consumption models into a scheduling optimization problem. An effective parameterization of the time variables reduces the model complexity, allowing the optimizer to reschedule the complete sequence of operations for minimizing the total energy consumption, while keeping a fixed cycle time. The method has been integrated into a commercial tool for robot programming. The optimization is applicable both on new and existing robotic systems, since the required modifications are limited to the operations rescheduling, and no investments on new hardware are expected.
|
|
