In order to establish DED processes for different series sizes in vehicle production, it must be possible to store, process and securely provide a wide variety of data across the entire process chain. The data should also be utilised to add value by means of intelligent processes.

Industry
Automotive industry

Services
Scalable data storage
Data federation
Predictive maintenance




Quick Facts

12
Number of project partners
50
Number of employees
3
Project duration in years
20 %
Market growth in additive manufacturing per year

The challenge

The task of iSYS is to set up a distributed, replicated data storage system that can store a wide variety of object types efficiently and scalably and make them available at all process levels without jeopardising data integrity. In addition, iSYS is responsible for data modelling and model implementation, whereby structured and unstructured data as well as multimedia data types are used. A further objective is to standardise and prepare the data collected during the DED process for further analysis. Machine learning methods will then be used to analyse the data with the aim of gaining new insights for a priori maintenance of plant components (predictive maintenance). Decision-making aids are generated from the data in order to increase the quality standards of the components produced (predictive quality).


The solution

Development of a distributed, replicated data management system
A flexible data management system was modelled and implemented with different solutions. A distinction was made between master data and payloads in order to optimally map the differing requirements in terms of consistency, scaling and processing. Unsuitable technologies were discarded and the remaining candidates consolidated.
Standardisation and preparation of data
A contract-based standardisation system was developed for the data collected in the DED process, on the basis of which it can be standardised, processed and passed on for further analysis. The data federation was designed to be largely compatible with Gaia-X in order to be able to utilise any data spaces that may be established.
Predictive maintenance / quality
Machine learning methods were used to analyse the data with the aim of gaining new insights for a priori maintenance of system parts (predictive maintenance) and also to increase the quality standards of the components produced (predictive quality). The data obtained can be analysed interactively and visually.

Technologies used

About the research partners

Fritz Automation is automation taken to the next level. Fritz Automation supports technology and mechanical engineering companies worldwide on their path to digital transformation.

Volkswagen Aktiengesellschaft, based in Wolfsburg, Lower Saxony, is a German car manufacturer and the largest car manufacturer in the world in terms of sales generated.

AGCO has set itself the goal of developing and distributing agricultural solutions for sustainably feeding the world. The success of farmers is at the centre of all activities of the company and its brands.

The KÖNIG METALL Group has been processing customised sheet metal and tubes for the metal and electrical industries, the automotive, silencer and airbag industries, for mechanical engineering and various other sectors at 8 locations worldwide for over 100 years.

Siemens AG is a German conglomerate with a focus on automation and digitalisation in industry, infrastructure for buildings, decentralised energy systems, mobility solutions for rail and road transport and medical technology.

Automation W+R is a provider of turnkey solutions in industrial image processing and for the automation of quality assurance

Boll Automation GmbH is part of the Autision Group GmbH. The robotics specialists make innovative solutions in the field of handling and post-processing possible by combining sensor technology with measurement technology.

roehren GmbH has been advising manufacturing companies since 2011 and has built up experience in production optimisation in 47 countries.

applicationtechnology provides support in the areas of production process optimisation, prototype construction, small series production, employee training and online and offline robot programming. The company specialises in laser beam welding, laser beam soldering and laser beam cutting.

As one of the largest production technology research institutions in Germany, the iwb comprises three chairs of the TUM School of Engineering and Design in Garching near Munich. The iwb’s research content and key topics are in the areas of additive manufacturing, battery production, laser technology, assembly technology and robotics, sustainable production, production management and logistics, as well as machine tools.

The Precitec Group is a global innovation and market leader in the development and manufacture of components and system solutions in the field of laser technology and optical metrology.

Forschungsprogramm

Funded by: Federal Ministry for Economic Affairs and Climate Protection based on a resolution of the German Bundestag


Do you have any questions? We will be happy to help you!

Do you have a project that you would like to talk to us about? You are welcome to contact us at any time. We look forward to getting to know you!

Marc Ponschab
Marc Ponschab Head of Technology Lab / R&D