Energy-efficient robot applications towards sustainable manufacturing
| Autor: | Abdullah Mohammed, Lihui Wang, Bernard Schmidt, Xi Vincent Wang |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Engineering energy-efficiency robot configuration Aerospace Engineering Context (language use) Cloud computing 02 engineering and technology Computer Science::Robotics 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Cloud manufacturing cloud manufacturing business.industry Mechanical Engineering Sustainable manufacturing 020208 electrical & electronic engineering Control engineering Robotics Energy consumption Manufacturing engineering robotic assembly Computer Science Applications Robotteknik och automation trajectory Robot Artificial intelligence business Efficient energy use |
| Zdroj: | International Journal of Computer Integrated Manufacturing. 31:692-700 |
| ISSN: | 1362-3052 0951-192X |
| DOI: | 10.1080/0951192x.2017.1379099 |
| Popis: | The cloud technology provides sustainable solutions to the modern industrial robotic cells. Within the context, the objective of this research is to minimise the energy consumption of robots during assembly in a cloud environment. Given a robot path and based on the inverse kinematics and dynamics of the robot from the cloud, a set of feasible configurations of the robot can be derived, followed by calculating the desirable forces and torques on the joints and links of the robot. Energy consumption is then calculated for each feasible configuration along the path. The ones with the lowest energy consumption are chosen. Since the energy-efficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be applied to energy-efficient robotic assembly. This cloud-based energy-efficient approach for robotic applications can largely enhance the current practice as demonstrated by the results of three case studies, leading towards sustainable manufacturing. CC BY 3.0 |
| Databáze: | OpenAIRE |
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