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@Article { Jakobs_2023_3,
   title = {Preserving the Royalty-Free Standards Ecosystem},
   journal = {European Intellectual Property Review},
   year = {2023},
   month = {7},
   volume = {45},
   number = {7},
   pages = {371-375},
   abstract = {It has long been recognized in Europe and elsewhere that standards-development organizations (SDOs) may adopt policies that require their participants to license patents essential to the SDO’s standards (standards-essential patents or SEPs) to manufacturers of standardized products (“implementers”) on a royalty-free (RF) basis. This requirement contrasts with SDO policies that permit SEP holders to charge implementers monetary patent royalties, sometimes on terms that are specified as “fair, reasonable and nondiscriminatory” (FRAND). As demonstrated by two decades of intensive litigation around the world, FRAND royalties have given rise to intractable disputes regarding the manner in which such royalties should be calculated and adjudicated. In contrast, standards distributed on an RF basis are comparatively free from litigation and the attendant transaction costs. Accordingly, numerous SDOs around the world have adopted RF licensing policies and many widely adopted standards, including Bluetooth, USB, IPv6, HTTP, HTML and XML, are distributed on an RF basis. This note briefly discusses the commercial considerations surrounding RF standards, the relationship between RF standards and open source software (OSS) and the SDO policy mechanisms – including “universal reciprocity” -- that enable RF licensing to succeed in the marketplace.},
   ISSN = {0142-0461},
   DOI = {10.2139/ssrn.4235647},
   reviewed = {1},
   author = {Contreras, Jorge and Bekkers, Rudi and Biddle, Brad and Bonadio, Enrico and Carrier, Michael A. and Chao, Bernard and Duan, Charles and Gilbert, Richard and Henkel, Joachim and Hovenkamp, Erik and Husovec, Martin and Jakobs, Kai and Kim, Dong-hyu and Lemley, Mark A. and Love, Brian J. and McDonagh, Luke and Scott Morton, Fiona M. and Schultz, Jason and Simcoe, Timothy and Urban, Jennifer M. and Xiang, Joy Y}
}

@Incollection { 2023_rueppel_crd-b2.ii,
   title = {Model-Based Controlling Approaches for Manufacturing Processes},
   year = {2023},
   month = {2},
   day = {8},
   pages = {221-246},
   abstract = {The main objectives in production technology are quality assurance, cost reduction, and guaranteed process safety and stability. Digital shadows enable a more comprehensive understanding and monitoring of processes on shop floor level. Thus, process information becomes available between decision levels, and the aforementioned criteria regarding quality, cost, or safety can be included in control decisions for production processes. The contextual data for digital shadows typically arises from heterogeneous sources. At shop floor level, the proximity to the process requires usage of available data as well as domain knowledge. Data sources need to be selected, synchronized, and processed. Especially high-frequency data requires algorithms for intelligent distribution and efficient filtering of the main information using real-time devices and in-network computing. Real-time data is enriched by simulations, metadata from product planning, and information across the whole process chain. Well-established analytical and empirical models serve as the base for new hybrid, gray box approaches. These models are then applied to optimize production process control by maximizing the productivity under given quality and safety constraints. To store and reuse the developed models, ontologies are developed and a data lake infrastructure is utilized and constantly enlarged laying the basis for a World Wide Lab (WWL). Finally, closing the control loop requires efficient quality assessment, immediately after the process and directly on the machine. This chapter addresses works in a connected job shop to acquire data, identify and optimize models, and automate systems and their deployment in the Internet of Production (IoP).},
   keywords = {Process control; Model-based control; Data aggregation; Model identification; Model optimization},
   tags = {internet-of-production},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-rueppel-iop-b2.i.pdf},
   publisher = {Springer},
   series = {Interdisciplinary Excellence Accelerator Series},
   booktitle = {Internet of Production: Fundamentals, Applications and Proceedings},
   ISBN = {978-3-031-44496-8},
   DOI = {10.1007/978-3-031-44497-5_7},
   reviewed = {1},
   author = {R{\"u}ppel, Adrian Karl and Ay, Muzaffer and Biernat, Benedikt and Kunze, Ike and Landwehr, Markus and Mann, Samuel and Pennekamp, Jan and Rabe, Pascal and Sanders, Mark P. and Scheurenberg, Dominik and Schiller, Sven and Xi, Tiandong and Abel, Dirk and Bergs, Thomas and Brecher, Christian and Reisgen, Uwe and Schmitt, Robert H. and Wehrle, Klaus}
}

@Inproceedings { 2020_pennekamp_parameter_exchange,
   title = {Privacy-Preserving Production Process Parameter Exchange},
   year = {2020},
   month = {12},
   day = {10},
   pages = {510-525},
   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.},
   keywords = {secure industrial collaboration; Bloom filter; oblivious transfer; Internet of Production},
   tags = {internet-of-production},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-pennekamp-parameter-exchange.pdf},
   publisher = {ACM},
   booktitle = {Proceedings of the 36th Annual Computer Security Applications Conference (ACSAC '20), December 7-11, 2020, Austin, TX, USA},
   event_place = {Austin, TX, USA},
   event_date = {December 7-11, 2020},
   ISBN = {978-1-4503-8858-0/20/12},
   DOI = {10.1145/3427228.3427248},
   reviewed = {1},
   author = {Pennekamp, Jan and Buchholz, Erik and Lockner, Yannik and Dahlmanns, Markus and Xi, Tiandong and Fey, Marcel and Brecher, Christian and Hopmann, Christian and Wehrle, Klaus}
}

@Inproceedings { 2012-AIS-Gerst-vehicles,
   title = {Electric Vehicles and Standardization Management – The Case of a Sino-German Cooperation},
   year = {2012},
   month = {6},
   day = {8},
   booktitle = {Proc. of the Annual Conference of the Academy of Innovation and Entrepreneurship (AIS).},
   author = {Gerst, Martina and Jakobs, Kai and Xudong, Gao}
}