Engineering news
From left: Dr Kristofer Bengtsson, master’s student Emma Vidarsson and Professor Bengt Lennartson in the Robotics and Automation Laboratory at Chalmers University of Technology.
An algorithm that minimises the acceleration of industrial robots can reduce energy consumption by up to 40 percent without impacting production time, say researchers from Chalmers University of Technology in Switzerland.
In robot-intensive manufacturing industries, such as bodywork factories in the automotive industry, robots consume about half of the total energy used for production. Optimisation of the robot's movements reduces acceleration and deceleration, as well as the time the robot is at a standstill, which also consumes energy.
Professor Bengt Lennartson, who initiated the research together along with industrial partners including General Motors, said: “We simply let the robot move slower instead of waiting for other robots and machines to catch up before carrying out the next sequence. The optimisation also determines the order in which the various operations are carried out to minimise energy consumption – without reducing the total execution time.”
The optimisation does not change the robot’s operation path, only the speed and sequence. As such, the researchers were able to go into an existing robot cell and perform a “quick optimisation” without impacting production or the current cycle.
To achieve safe optimisation, several robots moving in the same area need to be coordinated. The optimisation tool initially identifies where robots may collide, and the entry and exit positions for each collision zone, and for each robot path.
Kristofer Bengtsson, who is responsible for the implementation of the new optimisation strategy, said: “The first test results have shown a significant improvement, such as a 15 to 40 percent energy reduction, but the results are still preliminary. In order to estimate the actual energy savings, further testing in industry is required.”
The optimisation program starts by logging the movements of each robot during an operations cycle, as well as any collision zones. This information is processed by the optimiser, which generates new control instructions that can be directly executed by the robots.
Bengtsson said: “The goal is to make this kind of optimisation standard, and included in robots from the start. At each adjustment of the operating sequences, a new optimisation is conducted by default. But as we all know, it takes time to bring a development product into a robust production process, with several years of engineering work.”