Inline production and quality control during milling of metallic and CFK production applications
In the MAI ILQ 2020 project, the University of Augsburg, together with the project partners BMW and Hufschmied Zerspanungssysteme GmbH, is working out how the quality in milling processes (In-Line Quality, ILQ for short) can be improved through the cross-company exchange of data. The technological process data and the data from quality control will be linked in such a way that a meaningful component and process data mapping for the partners is created, which sufficiently protects their own technological know-how and thus satisfies the company’s own need for security. By exchanging the data, both companies hope to be able to build better products and reduce production costs.
|Kurzbezeichnung||MAI ILQ 2020|
|Förderung||Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie|
|Projektträger||VDI/ VDE/ IT|
|Förderprogramm||Informations- und Kommunikationstechnik|
|Fördernummer laut Bescheid||IUK-1802-0008//IUK569/005|
|Projektleitung||Prof. Dr. Henner Gimpel|
Background and Objective of the Project
Industrial companies hope to be able to use the potential of digitisation and to do a lot better with the help of data. Some people are even talking about the fourth industrial revolution, or Industry 4.0 for short, which would enable companies not only to save costs but also to open up new business areas, create jobs and conserve resources in an environmentally friendly way. However, if you do a little research, you quickly come across many unanswered questions. What data already exists in my company? Which data is required? Where is the data? What knowledge worth protecting is behind the data? Do I want to disclose this knowledge? Which threat scenarios can arise from the cross-company data exchange? Which protective measures can companies use to arm themselves against them? And which trade-off do I have to take? The “MAI ILQ 2020” project deals with these questions.
MAI ILQ 2020 | Paper published
Towards Trustworthy, Cross-Company, Automated Data Exchange Between Machines – Identification of Know-How Worthy of Protection in the Age of Industry 4.0