Projects

The project aims to digitalize established tools for production disturbance handling.

2018 – 2020

Improve the efficiency of sawmills, including improved monitoring and maintenance of the production line. This by sharing data via digital twin between the actors in the maintenance chain.

2019 – 2019

Maintenance in existing plants is becoming increasingly important, where predictive maintenance has become an emerging technology. The use of decision support tools contributes to environmentally and economically sustainable production. Within this project, different types of digital twins have been designed and evaluated. Specifically, new predictive model types have been tested in two different industrial case studies; a heat exchanger at SSAB and a profiled header at Svenska Fönster AB.

2017 – 2018

En hållbar batterisektor i Sverige genom effektivt underhåll av framtidens batteriproduktion.

2022 – 2023

To create an inventory of AI techniques for maintenance services, apply AI techniques to three industrial cases, and evaluate their economic and environmental implications.

2017 – 2019

The project aims at facilitating the implementation of Smart Maintenance through extended collaboration within the maintenance community.

2017 – 2019

Recent research from Chalmers have shown that by slightly tuning robot motions, the energy use can be reduced by 10 –30%, with preserved cycle time.

2017 – 2020

The objective is to bring together expertise from AI and LCE to Product/Service Systems for Swedish manufacturing firms in a multidisciplinary research effort to utilise latest techniques efficiently for Swedish production industry. The goal is to make a plan of developing demonstrators in production and maintenance using artificial intelligence techniques, digital technologies and lifecycle engineering methods

2019 – 2019

To demonstrate the new technology with robots that enable Swedish companies to develop innovative new products for automated production o maintenance.

2017 – 2020