This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2020-10-24 Creation time: 20-33-45 --- Number of references 8 article 2020_niemietz_stamping Procedia Manufacturing 2020 7 11 49 61-68 Sharing data between companies throughout the supply chain is expected to be beneficial for product quality as well as for the economical savings in the manufacturing industry. To utilize the available data in the vision of an Internet of Production (IoP) a precise condition monitoring of manufacturing and production processes that facilitates the quantification of influences throughout the supply chain is inevitable. In this paper, we consider stamping processes in the context of an Internet of Production and the preliminaries for analytical models that utilize the ever-increasing available data. Three research objectives to cope with the amount of data and for a methodology to monitor, analyze and evaluate the influence of available data onto stamping processes have been identified: (i) State detection based on cyclic sensor signals, (ii) mapping of in- and output parameter variations onto process states, and (iii) models for edge and in-network computing approaches. After discussing state-of-the-art approaches to monitor stamping processes and the introduction of the fineblanking process as an exemplary stamping process, a research roadmap for an IoP enabling modeling framework is presented. Proceedings of the 8th International Conference on Through-Life Engineering Service (TESConf '19), October 27-29, 2019, Cleveland, OH, USA Stamping Process; Industry 4.0; Fine-blanking; Internet of production; Condition monitoring; Data analytics internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-niemietz-stamping-modelling.pdf Elsevier 2351-9789 10.1016/j.promfg.2020.06.012 1 PhilippNiemietz JanPennekamp IkeKunze DanielTrauth KlausWehrle ThomasBergs inproceedings 2020_buckhorst_lmas 2020 7 Assembly systems must provide maximum flexibility qualified by organization and technology to offer cost-compliant performance features to differentiate themselves from competitors in buyers’ markets. By mobilization of multipurpose resources and dynamic planning, Line-less Mobile Assembly Systems (LMASs) offer organizational reconfigurability. By proposing a holarchy to combine LMASs with the concept of an Internet of Production (IoP), we enable LMASs to source valuable information from cross-level production networks, physical resources, software nodes, and data stores that are interconnected in an IoP. The presented holarchy provides a concept of how to address future challenges, meet the requirements of shorter lead times, and unique lifecycle support. The paper suggests an application of decision making, distributed sensor services, recommender-based data reduction, and in-network computing while considering safety and human usability alike. Internet of Production; Line-less Mobile Assembly System; Industrial Assembly; Smart Factory internet-of-production https://jpennekamp.de/wp-content/papercite-data/pdf/bmw+20.pdf Elsevier Proceedings of the 14th CIRP Conference on Intelligent Computation in Manufacturing Engineering (ICME '20), July 14-17, 2020, Gulf of Naples, Italy Gulf of Naples, Italy July 14-17, 2020 accepted 1 Armin F.Buckhorst BenjaminMontavon DominikWolfschläger MelanieBuchsbaum AmirShahidi HenningPetruck IkeKunze JanPennekamp ChristianBrecher MathiasHüsing BurkhardCorves VerenaNitsch KlausWehrle Robert H.Schmitt inproceedings 2020-mann-ur-weldseamstudy 2020 6 https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-mann-weld-seam-geometry-control.pdf Proceedings of the 2020 Internal Conference on Ubiquitous Robots Internal Conference on Ubiquitous Robots June 22-26, 2020 accepted 10.1109/UR49135.2020.9144839 1 SamuelMann RenéGlebke IkeKunze DominikScheurenberg RahulSharma UweReisgen KlausWehrle DirkAbel article 2019-kunze-ccwild-tnsm IEEE Transactions on Network and Service Management 2019 12 27 17 2 1224 - 1238 https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-kunze-ccwild-tnsm.pdf 1932-4537 10.1109/TNSM.2019.2962607 1 IkeKunze JanRüth OliverHohlfeld inproceedings 2019-glebke-in-network-cv 2019 12 9 reflexes,maki,internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-glebke-in-network-cv.pdf Online ACM 1st ACM CoNEXT Workshop on Emerging in-Network Computing Paradigms (ENCP '19) en 978-1-4503-7000-4/19/12 10.1145/3359993.3366646 1 RenéGlebke JohannesKrude IkeKunze JanRüth FelixSenger KlausWehrle inproceedings 2019-rueth-ccfness 2019 6 19 maki https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-rueth-ccfness.pdf https://arxiv.org/abs/1905.07152 IFIP/IEEE In Proceedings of the Network Traffic Measurement and Analysis Conference (TMA '19) Paris, France Network Traffic Measurement and Analysis Conference 19.06.2019 - 21.06.2019 10.23919/TMA.2019.8784684 1 JanRüth IkeKunze OliverHohlfeld article rueth:iw:TNSM19 IEEE Transactions on Network and Service Management 2019 1 30 16 2 389--402 maki http://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-rueth-iwtnsm.pdf 1932-4537 10.1109/TNSM.2019.2896335 1 JanRüth IkeKunze OliverHohlfeld article 2017-ziegeldorf-bmcmedgenomics-bloom BMC Medical Genomics 2017 7 26 10 Suppl 2 29-42 Whole genome sequencing has become fast, accurate, and cheap, paving the way towards the large-scale collection and processing of human genome data. Unfortunately, this dawning genome era does not only promise tremendous advances in biomedical research but also causes unprecedented privacy risks for the many. Handling storage and processing of large genome datasets through cloud services greatly aggravates these concerns. Current research efforts thus investigate the use of strong cryptographic methods and protocols to implement privacy-preserving genomic computations. We propose FHE-Bloom and PHE-Bloom, two efficient approaches for genetic disease testing using homomorphically encrypted Bloom filters. Both approaches allow the data owner to securely outsource storage and computation to an untrusted cloud. FHE-Bloom is fully secure in the semi-honest model while PHE-Bloom slightly relaxes security guarantees in a trade-off for highly improved performance. We implement and evaluate both approaches on a large dataset of up to 50 patient genomes each with up to 1000000 variations (single nucleotide polymorphisms). For both implementations, overheads scale linearly in the number of patients and variations, while PHE-Bloom is faster by at least three orders of magnitude. For example, testing disease susceptibility of 50 patients with 100000 variations requires only a total of 308.31 s (σ=8.73 s) with our first approach and a mere 0.07 s (σ=0.00 s) with the second. We additionally discuss security guarantees of both approaches and their limitations as well as possible extensions towards more complex query types, e.g., fuzzy or range queries. Both approaches handle practical problem sizes efficiently and are easily parallelized to scale with the elastic resources available in the cloud. The fully homomorphic scheme, FHE-Bloom, realizes a comprehensive outsourcing to the cloud, while the partially homomorphic scheme, PHE-Bloom, trades a slight relaxation of security guarantees against performance improvements by at least three orders of magnitude. Proceedings of the 5th iDASH Privacy and Security Workshop 2016 Secure outsourcing; Homomorphic encryption; Bloom filters sscilops,mynedata https://www.comsys.rwth-aachen.de/fileadmin/papers/2017/2017-ziegeldorf-bmcmedgenomics-bloom.pdf Online BioMed Central Chicago, IL, USA November 11, 2016 en 1755-8794 10.1186/s12920-017-0277-y 1 Jan HenrikZiegeldorf JanPennekamp DavidHellmanns FelixSchwinger IkeKunze MartinHenze JensHiller RomanMatzutt KlausWehrle