% % This file was created by the TYPO3 extension % bib % --- Timezone: CEST % Creation date: 2024-07-04 % Creation time: 08-26-30 % --- Number of references % 9 % @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} } @Incollection { 2023_klugewilkes_crd-b2.iv, title = {Modular Control and Services to Operate Line-less Mobile Assembly Systems}, year = {2023}, month = {2}, day = {8}, pages = {303-328}, abstract = {The increasing product variability and lack of skilled workers demand for autonomous, flexible production. Since assembly is considered a main cost driver and accounts for a major part of production time, research focuses on new technologies in assembly. The paradigm of Line-less Mobile Assembly Systems (LMAS) provides a solution for the future of assembly by mobilizing all resources. Thus, dynamic product routes through spatiotemporally configured assembly stations on a shop floor free of fixed obstacles are enabled. In this chapter, we present research focal points on different levels of LMAS, starting with the macroscopic level of formation planning, followed by the mesoscopic level of mobile robot control and multipurpose input devices and the microscopic level of services, such as interpreting autonomous decisions and in-network computing. We provide cross-level data and knowledge transfer through a novel ontology-based knowledge management. Overall, our work contributes to future safe and predictable human-robot collaboration in dynamic LMAS stations based on accurate online formation and motion planning of mobile robots, novel human-machine interfaces and networking technologies, as well as trustworthy AI-based decisions.}, keywords = {Lineless mobile assembly systems (LMAS); Formation planning; Online motion planning; In-network computing; Interpretable AI; Human-machine collaboration; Ontology-based knowledge management}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-klugewilkes-iop-b2.iv.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_13}, reviewed = {1}, author = {Kluge-Wilkes, Aline and Baier, Ralph and Gossen, Daniel and Kunze, Ike and M{\"u}ller, Aleksandra and Shahidi, Amir and Wolfschl{\"a}ger, Dominik and Brecher, Christian and Corves, Burkhard and H{\"u}sing, Mathias and Nitsch, Verena and Schmitt, Robert H. and Wehrle, Klaus} } @Article { 2021_buckhorst_lmas, title = {Holarchy for Line-less Mobile Assembly Systems Operation in the Context of the Internet of Production}, journal = {Procedia CIRP}, year = {2021}, month = {5}, day = {3}, volume = {99}, pages = {448-453}, abstract = {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.}, note = {Proceedings of the 14th CIRP Conference on Intelligent Computation in Manufacturing Engineering (ICME '20), July 14-17, 2020, Gulf of Naples, Italy}, keywords = {Internet of Production; Line-less Mobile Assembly System; Industrial Assembly; Smart Factory}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2021/2021-buckhorst-holarchy.pdf}, publisher = {Elsevier}, event_place = {Gulf of Naples, Italy}, event_date = {July 14-17, 2020}, ISSN = {2212-8271}, DOI = {10.1016/j.procir.2021.03.064}, reviewed = {1}, author = {Buckhorst, Armin F. and Montavon, Benjamin and Wolfschl{\"a}ger, Dominik and Buchsbaum, Melanie and Shahidi, Amir and Petruck, Henning and Kunze, Ike and Pennekamp, Jan and Brecher, Christian and H{\"u}sing, Mathias and Corves, Burkhard and Nitsch, Verena and Wehrle, Klaus and Schmitt, Robert H.} } @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} } @Article { 2020_gleim_factDAG, title = {FactDAG: Formalizing Data Interoperability in an Internet of Production}, journal = {IEEE Internet of Things Journal}, year = {2020}, month = {4}, day = {14}, volume = {7}, number = {4}, pages = {3243-3253}, abstract = {In the production industry, the volume, variety and velocity of data as well as the number of deployed protocols increase exponentially due to the influences of IoT advances. While hundreds of isolated solutions exist to utilize this data, e.g., optimizing processes or monitoring machine conditions, the lack of a unified data handling and exchange mechanism hinders the implementation of approaches to improve the quality of decisions and processes in such an interconnected environment. The vision of an Internet of Production promises the establishment of a Worldwide Lab, where data from every process in the network can be utilized, even interorganizational and across domains. While numerous existing approaches consider interoperability from an interface and communication system perspective, fundamental questions of data and information interoperability remain insufficiently addressed. In this paper, we identify ten key issues, derived from three distinctive real-world use cases, that hinder large-scale data interoperability for industrial processes. Based on these issues we derive a set of five key requirements for future (IoT) data layers, building upon the FAIR data principles. We propose to address them by creating FactDAG, a conceptual data layer model for maintaining a provenance-based, directed acyclic graph of facts, inspired by successful distributed version-control and collaboration systems. Eventually, such a standardization should greatly shape the future of interoperability in an interconnected production industry.}, keywords = {Data Management; Data Versioning; Interoperability; Industrial Internet of Things; Worldwide Lab}, tags = {internet-of-production}, url = {https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-gleim-iotj-iop-interoperability.pdf}, publisher = {IEEE}, ISSN = {2327-4662}, DOI = {10.1109/JIOT.2020.2966402}, reviewed = {1}, author = {Gleim, Lars and Pennekamp, Jan and Liebenberg, Martin and Buchsbaum, Melanie and Niemietz, Philipp and Knape, Simon and Epple, Alexander and Storms, Simon and Trauth, Daniel and Bergs, Thomas and Brecher, Christian and Decker, Stefan and Lakemeyer, Gerhard and Wehrle, Klaus} } @Article { 2020-wehrle-digitalshadows, title = {Mit ''Digitalen Schatten'' Daten verdichten und darstellen : Der Exzellenzcluster ''Internet der Produktion'' forscht {\"u}ber die Produktionstechnik hinaus}, journal = {Der Profilbereich ''Information \& Communication Technology''}, year = {2020}, ISSN = {0179-079X}, DOI = {10.18154/RWTH-2021-02496}, author = {Jarke, Matthias and van der Aalst, Wil and Brecher, Christian and Brockmann, Matthias and Koren, Istv{\'a}n and Lakemeyer, Gerhard and Rumpe, Bernhard and Schuh, G{\"u}nther and Wehrle, Klaus and Ziefle, Martina} } @Inproceedings { 2019_pennekamp_dataflows, title = {Dataflow Challenges in an Internet of Production: A Security \& Privacy Perspective}, year = {2019}, month = {11}, day = {11}, pages = {27-38}, abstract = {The Internet of Production (IoP) envisions the interconnection of previously isolated CPS in the area of manufacturing across institutional boundaries to realize benefits such as increased profit margins and product quality as well as reduced product development costs and time to market. This interconnection of CPS will lead to a plethora of new dataflows, especially between (partially) distrusting entities. In this paper, we identify and illustrate these envisioned inter-organizational dataflows and the participating entities alongside two real-world use cases from the production domain: a fine blanking line and a connected job shop. Our analysis allows us to identify distinct security and privacy demands and challenges for these new dataflows. As a foundation to address the resulting requirements, we provide a survey of promising technical building blocks to secure inter-organizational dataflows in an IoP and propose next steps for future research. Consequently, we move an important step forward to overcome security and privacy concerns as an obstacle for realizing the promised potentials in an Internet of Production.}, keywords = {Internet of Production; dataflows; Information Security}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-pennekamp-dataflows.pdf}, publisher = {ACM}, booktitle = {Proceedings of the 5th ACM Workshop on Cyber-Physical Systems Security and PrivaCy (CPS-SPC '19), co-located with the 26th ACM SIGSAC Conference on Computer and Communications Security (CCS '19), November 11-15, 2019, London, United Kingdom}, event_place = {London, United Kingdom}, event_date = {November 11-15, 2019}, ISBN = {978-1-4503-6831-5/19/11}, DOI = {10.1145/3338499.3357357}, reviewed = {1}, author = {Pennekamp, Jan and Henze, Martin and Schmidt, Simo and Niemietz, Philipp and Fey, Marcel and Trauth, Daniel and Bergs, Thomas and Brecher, Christian and Wehrle, Klaus} } @Inproceedings { 2019_pennekamp_infrastructure, title = {Towards an Infrastructure Enabling the Internet of Production}, year = {2019}, month = {5}, day = {8}, pages = {31-37}, abstract = {New levels of cross-domain collaboration between manufacturing companies throughout the supply chain are anticipated to bring benefits to both suppliers and consumers of products. Enabling a fine-grained sharing and analysis of data among different stakeholders in an automated manner, such a vision of an Internet of Production (IoP) introduces demanding challenges to the communication, storage, and computation infrastructure in production environments. In this work, we present three example cases that would benefit from an IoP (a fine blanking line, a high pressure die casting process, and a connected job shop) and derive requirements that cannot be met by today’s infrastructure. In particular, we identify three orthogonal research objectives: (i) real-time control of tightly integrated production processes to offer seamless low-latency analysis and execution, (ii) storing and processing heterogeneous production data to support scalable data stream processing and storage, and (iii) secure privacy-aware collaboration in production to provide a basis for secure industrial collaboration. Based on a discussion of state-of-the-art approaches for these three objectives, we create a blueprint for an infrastructure acting as an enabler for an IoP.}, keywords = {Internet of Production; Cyber-Physical Systems; Data Processing; Low Latency; Secure Industrial Collaboration}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-pennekamp-iop-infrastructure.pdf}, publisher = {IEEE}, booktitle = {Proceedings of the 2nd IEEE International Conference on Industrial Cyber-Physical Systems (ICPS '19), May 6-9, 2019, Taipei, TW}, event_place = {Taipei, TW}, event_date = {May 6-9, 2019}, ISBN = {978-1-5386-8500-6/19}, DOI = {10.1109/ICPHYS.2019.8780276}, reviewed = {1}, author = {Pennekamp, Jan and Glebke, Ren{\'e} and Henze, Martin and Meisen, Tobias and Quix, Christoph and Hai, Rihan and Gleim, Lars and Niemietz, Philipp and Rudack, Maximilian and Knape, Simon and Epple, Alexander and Trauth, Daniel and Vroomen, Uwe and Bergs, Thomas and Brecher, Christian and B{\"u}hrig-Polaczek, Andreas and Jarke, Matthias and Wehrle, Klaus} } @Proceedings { 2017-serror-netsys-industrial, title = {Demo: A Realistic Use-case for Wireless Industrial Automation and Control}, year = {2017}, month = {3}, day = {16}, tags = {koi}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2017/Ansari_et_al_Wireless_Industrial_Automation_Demo_NetSys_2017.pdf}, publisher = {IEEE}, event_place = {G{\"o}ttingen, Germany}, event_name = {International Conference on Networked Systems (NetSys 2017)}, DOI = {10.1109/NetSys.2017.7931496}, reviewed = {1}, author = {Ansari, Junaid and Aktas, Ismet and Brecher, Christian and Pallasch, Christoph and Hoffmann, Nicolai and Obdenbusch, Markus and Serror, Martin and Wehrle, Klaus and Gross, James} }