Towards Safe Service Ecosystems for Production for Value Networks and Manufacturing Monitoring
 
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1
Fraunhofer Institute for Machine Tools and Forming Technology (IWU), Dresden
 
2
Technische Universität Dresden – Institute of Software and Multimedia Technology, Dresden
 
3
Technische Universität Dresden – Chair of machine tools development and adaptive controls, Dresden
 
 
Submission date: 2019-11-22
 
 
Acceptance date: 2020-02-03
 
 
Online publication date: 2020-02-26
 
 
Publication date: 2020-03-06
 
 
Journal of Machine Engineering 2020;20(1):117-126
 
KEYWORDS
TOPICS
ABSTRACT
In a global sales market with networked production steps and increasing complex machine tools, scaling service ecosystems for production provide an adequate solution for handling the generated data. The existing sensor equipment at current and the extension possibility by the System-of-Systems approach for existing machine tools can offer value-added services by the smart handling of production-related data. It is important to make these data validatable and exchangeable, taking into account to different protection goals. The trust of the individual actors in such a volatile value chain and the different (partly cross-border) value creation partners play an important role. The participation of a large number of these actors creates an attractive overall system (ecosystem) with lots of services and network effects. Concerning data security there are numerous aspects, which have not been adequately answered or taken into account in the use of a service ecosystem in the production environment. The paper discusses a distributed ecosystem for production on a distributed ledger-based service ecosystem, in which services can be mapped in the machine tool environment (e.g. calibration). This technology can be used for secure data exchange in order to discuss traceability and unchangeability of data while maintaining data sovereignty.
ACKNOWLEDGEMENTS
This Paper has been financed by BMWi Program “Smarte Datenwirtschaft” – Project “AUDlo-Auditlösung für ML-basierte, datengetriebene Dienstleistungen” Reg.-Nr.: 01MD19005, Germany. It was supported by the Federal Ministry for Economic Affairs and Energy (BMWi) based on a decision taken by the German Bundestag. This work was also supported by the Fraunhofer Internal Programmes under Grant No. MEF 836273.
 
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