Privacy-Preserving Production Process Parameter Exchange
Abstract
Nowadays, collaborations between industrial companies always go hand in hand with trust issues, i.e., exchanging valuable production data entails the risk of improper use of potentially sensitive information. Therefore, companies hesitate to offer their production data, e.g., process parameters that would allow other companies to establish new production lines faster, against a quid pro quo. Nevertheless, the expected benefits of industrial collaboration, data exchanges, and the utilization of external knowledge are significant. In this paper, we introduce our Bloom filter-based Parameter Exchange (BPE), which enables companies to exchange process parameters privacy-preservingly. We demonstrate the applicability of our platform based on two distinct real-world use cases: injection molding and machine tools. We show that BPE is both scalable and deployable for different needs to foster industrial collaborations. Thereby, we reward data-providing companies with payments while preserving their valuable data and reducing the risks of data leakage.
Dr. rer. nat. Jan Pennekamp
Postdoctoral Researcher
Erik Buchholz
Yannik Lockner
Markus Dahlmanns, M.Sc.
Researcher
Tiandong Xi
Marcel Fey
Christian Brecher
Christian Hopmann
