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SDU behind database for robot assembly: Industrial companies must learn from their own and other companies’ data

31 MAY 2022

SDU behind database for robot assembly: Industrial companies must learn from their own and other companies' data

A new approach for gathering robotic experience from industry, so companies don’t have to start from scratch every time they need to put robots into production, has been launched – SDU is leading the project, which shall make better use of robotic data.

As robots and automation solutions increase in industrial companies, plans and project descriptions grow in numbers, often ending up in a digital folder on a company PC – if such data is stored at all. In most cases the data is never to be used again.

So is the reality today, but in the future, established solutions for automation, robots and data produced during the production process shall be reused, possibly even from other companies. In that way, companies do not have to design the complete solution from scratch themselves.

This is the ambition of the ReRoPro project (Re-Use of Robotic-data in Production through search, simulation and learning) which is funded by the national research centre DIREC and led by the Mærsk Mc-Kinney Møller Institute at SDU.

– Big data is already being used in the IT-field, where it has been crucial for developments in areas such as facial or object recognition. In the robotics field, there is great potential for gathering data and experience from companies that have already adopted new technology and automation in their production, says professor Norbert Krüger from the SDU Robotics at the Faculty of Engineering.

– Today, each company stores robot data – if at all – in their own format, but such data could just as well benefit others so that we can spread the use of robots and ultimately maintain or even attract production back to Denmark, he says.

Giants onboard

SDU is behind ReRoPro, together with Aalborg University and University of Copenhagen who also are partners in the DIREC project. The project also includes two Danish industrial giants, Novo Nordisk and Rockwool, the robotics company Nordbo from the Funen robotics cluster and the Allerød based company Welltec. Odense Robotics and MADE are also partners.

The ambition is to create a structure for a database with the help of the companies. We aim to gather information from existing solutions in such a structure that makes it possible to reuse or be inspired by that data when creating their own solution, says the SDU professor.

Novo Nordisk and Rockwool are already on board, but the intention is to get even more companies involved, Norbert Krüger stresses. That’s why a conference is planned for 8 September, where he hopes many industrial companies will come forward.

– For a lot of companies, this kind of data is considered a company secret, so we need to find a way how they can learn from each other in a safe environment. At the same time, we want to know more about what companies need out in the field so that we can take that into our work, says Norbert Krüger.

Initially, the project will run until autumn. Still, the plan is to outline a plan and invite industry along – via the conference – so that funding can then be secured for a significant research project based on the initial work, which is starting now.

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Read more about the project

FACTS

  • ReRoPro (Re-Use of Robotic-data in Production through search, simulation, and learning).

  • A new DIREC project headed by SDU in Odense with Aalborg and Copenhagen Universities involved. The ambition is to include many companies and already now the two Danish industrial giants, Novo Nordisk and Rockwool, and the robotics company Nordbo from the Funen robotics cluster as well as Welltech from Allerød are on board. Odense Robotics and MADE are also partners.

  • The initial project, funded by Innovation Fund Denmark, is to establish a structure for the database within six months, after which the ambition is to follow up with a larger project building the actual database and storing big data.

  • On 8 September, a conference is planned to gather companies and potential partners to discuss the ambitions and needs of industry.

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Young Researcher Entrepreneurship Bootcamp

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Young Researcher entrepreneurship bootcamp

Calling all young researchers in AI and data science with an interest in entrepreneurship!

Did you know that only 12-13% of PhDs end up in a tenure track academic career? The good news is that there are other exciting, fulfilling, flexible career paths, which you can shape yourself.

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The course specifically leverages AI, data science, and computer science in the service of societal and environmental challenges in for instance health-tech, green-tech, manufacturing, and business. The aim is to build entrepreneurial capacity and to increase the establishment of university-based startups.

Aarhus University is the host of YREB’23.   

The programme

The themes for each of the four days are as follows:

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The programme is co-developed by AAU, AU DTU, KU, DIREC and AI Pioneer Centre.

Target Group

We welcome PhD students and Post-doctoral researchers from computer/data related disciplines with little to no business experience from any Danish university.

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  • Being invited to pitching event at Digital Tech Summit November 8th – 9th 2023.
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Contemporary Computer Supported Cooperative Work Research

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Contemporary Computer Supported Cooperative Work Research

This PhD course is for PhD students conducting their research within the areas of Computer Supported Cooperative Work (CSCW) and Human Centred Design – currently working on positioning their research theoretically to push the boundaries for the novel and contemporary research contributions in CSCW research.

Contemporary CSCW research – How to create the literature scaffolding of contemporary CSCW PhD research which link to foundational aspects of CSCW while pushing the CSCW research into new contemporary areas of research.

Theoretical themes include (but not limited to) Articulation work & Coordination, Classifications & Categories, Awareness & Translucence; Infrastructures & Invisible Work; Knowledge Sharing & Common Information Spaces.

Learning outcome

  • Develop CSCW research questions looking to the past and thinking about the future
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After the course, students will have a foundational base for developing their theoretical research framework for their CSCW thesis – which both connects to the past, while focus on future contemporary directions.