Antingen stödjer din webbläsare inte javascript, eller är javascript inaktiverat. Denna webbplats fungerar bäst om du aktiverar javascript.

In addition, the development and maintenance work will be improved by the help of tools for condition monitoring and online prediction for maintenance planning. The overall aim is to reduce the energy usage of machines and robots with up to 30% and increase the life-time of the devices with more than 10%. Recent research results from Chalmers have shown that by tuning the motions of a robot slightly, the energy use can be reduced by 10-30%, while still preserving the cycle time. These tuned motions are smoother than the original motions, increasing the life-time of the robot and its components by reducing wear and tear.

The SmoothIT project thus aims to develop tools and methods to increase the awareness of energy usage and by that, realize design and decision support during virtual development to create sustainable motions. Tools and methods will also be developed that can monitor the production and identify motions that need to be improved or maintenance work that should be planned. In addition, online tools will be developed that can automatically optimize the production by tuning the motions to reduce the energy use and increase the lifetime of the devices.

The project is divided in three areas:

  1. virtual development and the digital twin,
  2. condition monitoring and maintenance, and
  3. online prediction and optimization.

In the first area, tools and methods will be developed in order to increase the awareness of energy usage and by that realize design and decision support during virtual development to create sustainable motions. The second area will develop tools and methods that can monitor the production and identify motions that need to be improved or maintenance work that should be planned. In the last area, online tools will be developed that can automatically optimize the production by tuning the motions to reduce the energy use and increase the lifetime of the devices. These three areas will support Swedish industry to improve all motions in production and make them sustainable.

The involved partners in the project are: Chalmers University of Technology, University West, Fraunhofer Chalmers Center, Volvo Car Corporation, AB Volvo, Scania, GKN and ABB. This project combines smart modelling, simulation, optimization, machine learning and data aggregation into a test bed, and develops a set of software tools that can be used by the industrial partners at the end of the project.

Forskningsområde

Teknik Produktionsteknik Produktionssystem

Forskningsmiljö / Institution

Produktionsteknik Väst, PTV Institutionen för ingenjörsvetenskap

Medverkande Högskolan Väst

Fredrik Danielsson Kristina Eriksson Sudha Ramasamy Xiaoxiao Zhang

Övriga projektmedverkande

Emile Glorieux

Forskningspartner

Chalmers tekniska högskola Volvo Cars ABB GKN Aerospace AB Volvo Fraunhofer Chalmers Center Scania

Forskningsfinansiär

Vinnova

Projekttid

2017 - 2020

Kontakt


Senast uppdaterad av Victoria Sjöstedt