Chalmers industrial robotic lab

Smoother movements reduce power peaks

​By programming industrial robots to operate more smoothly, and thus avoiding heavy accelerations and decelerations, energy consumption as well as power peaks can be significantly reduced. Based on these results, researchers are now taking a step further to investigate how other production equipment containing moving devices can be optimized.
​Designing optimal processes, while considering energy and environmental aspects, is becoming an increasingly important concern for the manufacturing industry. In the long run, it provides a competitive edge in terms of reduced production costs and a stronger sustainability profile.

Since several years, the research group Automation at Chalmers University of Technology has collaborated with the automotive industry to reduce energy consumption in robotic systems used in manufacturing processes. The industrial robots are energy-intensive. For example, in automotive bodywork factories the robots' consumption amounts to about half of the total energy used in production.

Lower energy demand and no production loss
”Our results show that the energy consumption can be reduced by 20-25 percent when industrial robots operate with smoother movements and avoid unnecessary starts and stops”, says Bengt Lennartson, Professor of Automation at the Department of Electrical Engineering. “And this without reducing the pace of production.”

The reduction is even greater when it comes to the robots´ power demands – the power peaks can be decreased by as much as 60 percent. As the powerconsuming accelerations are greatly reduced, in favour of a more balanced mode of driving, not as large momentary power demands occur. This also has a positive impact on the life-span of the components.

“The power demand being reduced to such high extent is a positive side effect of the energy saving we initially intended to achieve. So far, the power balance in the Swedish energy system has been good, but in the future, if the country is facing a situation where power shortage may occur, it will be expensive for industries whose electricity consumption is characterized by high power peaks.”

Bringing the method forward
“Our method for optimizing the robots has proved to be both simple and efficient,” says Bengt Lennartson. “The optimization never changes the robot’s operation path, only the speed and sequence. We collect data from the real robot and process it in an optimization program. The result is improved control instructions that are directly fed back to the robot.”

The research group has now started to apply their method in other fields of engineering as well, where there are moving and energy-intensive systems. This could include automated guided vehicles, conveyor systems and numerically controlled machining tools.

The production system of the future
The research on energy efficiency conducted by the Automation research group is a good example of computer-driven optimization methods. This type of optimization, combined with artificial intelligence, AI, is about to make its entry into industrial production to form what is known as Intelligent Manufacturing. It is about smart machines and connected manufacturing systems that interact and communicate with each other.

“Not least in China, there is a great interest in intelligent and sustainable production systems,” says Bengt Lennartson, who recently has participated as invited speaker in several research conferences on this topic. “Sweden is often mentioned as a good example of how sustainable and energy efficient manufacturing systems can be designed, and I agree that it really is our strength.

Text: Yvonne Jonsson
Photo: Malin Ulfvarson and Oscar Mattsson

More about the research

For more information, please contact:
Bengt Lennartson, Professor of Automation, Head of Division System and Control, Department of Electrical Engineering, Chalmers University of Technology, Sweden
Power consumption industrial robot























Reducing power peaks through minimizing accelerations in the robot movements.

Published: Thu 24 Jan 2019. Modified: Thu 24 Jan 2019