Prof. Dr.-Ing. Daniel Großmann

KNOLLMEYER, Simon, Oğuz CAYMAZER, Leonid KOVAL, Muhammad Uzair AKMAL, Saara ASIF, Selvine George MATHIAS und Daniel GROSSMANN, 2026. Evaluating Retrieval Augmented Generation: A Comprehensive Review of Evaluation Dimensions, Question Types, and Application. SN Computer Science, 7(5). ISSN 2661-8907. Verfügbar unter: https://doi.org/10.1007/s42979-026-05134-x

MAYR, Thomas, Simon KNOLLMEYER, Isidora JEKNIC, Leon FINK, Ralph HENSEL, Marco F. HUBER und Daniel GROSSMANN, 2026. Enhancing Process Planning in the Automotive Industry: Extracting Procedural Knowledge from Assembly Operation Descriptions using Large Language Models. Procedia CIRP, 2026(138), 797-802. ISSN 2212-8271. Verfügbar unter: https://doi.org/10.1016/j.procir.2026.01.137

AKMAL, Muhammad Uzair, Saara ASIF, Leonid KOVAL, Selvine George MATHIAS, Simon KNOLLMEYER und Daniel GROSSMANN, 2025. Layered Data-Centric AI to Streamline Data Quality Practices for Enhanced Automation. In: KOPRINKOVA-HRISTOVA, Petia und Nikola KASABOV, Hrsg. Artificial Intelligence: Methodology, Systems, and Applications: 19th International Conference, AIMSA 2024, Varna, Bulgaria, September 18–20, 2024, Proceedings. Cham: Springer, S. 128-142. ISBN 978-3-031-81542-3. Verfügbar unter: https://doi.org/10.1007/978-3-031-81542-3_11

MATHIAS, Selvine George, Saara ASIF, Muhammad Uzair AKMAL, Simon KNOLLMEYER, Leonid KOVAL und Daniel GROSSMANN, 2025. Industrial Image Grouping Through Pre-Trained CNN Encoder-Based Feature Extraction and Sub-Clustering. In: ROCHA, Ana Paula, Luc STEELS und Jaap VAN DEN HERIK, Hrsg. Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) - Volume 2. Setúbal: SciTePress, S. 496-506. ISBN 978-989-758-737-5. Verfügbar unter: https://doi.org/10.5220/0013189000003890

BILAL, Mühenad, Ranadheer PODISHETTI, Sri Girish TANGIRALA, Daniel GROSSMANN und Markus BREGULLA, 2025. CNN-Based Classification of Optically Critical Cutting Tools with Complex Geometry: New Insights for CNN-Based Classification Tasks. Sensors, 25(5), 1575. ISSN 1424-8220. Verfügbar unter: https://doi.org/10.3390/s25051575

KNOLLMEYER, Simon, Oğuz CAYMAZER und Daniel GROSSMANN, 2025. Document GraphRAG: Knowledge Graph Enhanced Retrieval Augmented Generation for Document Question Answering Within the Manufacturing Domain. Electronics, 14(11), 2102. ISSN 2079-9292. Verfügbar unter: https://doi.org/10.3390/electronics14112102

BILAL, Mühenad, Ranadheer PODISHETTI, Daniel GROSSMANN und Markus BREGULLA, 2025. Benchmarking CNN Architectures for Tool Classification: Evaluating CNN Performance on a Unique Dataset Generated by Novel Image Acquisition System. IEEE Access, 13, 96400-96422. ISSN 2169-3536. Verfügbar unter: https://doi.org/10.1109/ACCESS.2025.3574785

KOVAL, Leonid, Sonja WÄCHTER, Hüseyin ERDOGAN und Daniel GROSSMANN, 2025. Ontology-Driven Modeling and Integration of Production Processes in Advanced Driver-Assistance Systems within the Gaia-X Ecosystem. 2025 11th International Conference on Computer Technology Applications (ICCTA 2025). Piscataway: IEEE, S. 211-216. ISBN 979-8-3315-1265-1. Verfügbar unter: https://doi.org/10.1109/ICCTA65425.2025.11166225

KOVAL, Leonid, Muhammad Uzair AKMAL, Saara ASIF, Selvine George MATHIAS, Simon KNOLLMEYER und Daniel GROSSMANN, 2025. Optimizing AI-Driven Production in Industry 4.0: A Morphological Box and Taxonomy Approach. 2025 International Conference on Computer Technology Applications (ICCTA). Piscataway: IEEE, S. 272-278. ISBN 979-8-3315-1265-1. Verfügbar unter: https://doi.org/10.1109/ICCTA65425.2025.11166106

AKMAL, Muhammad Uzair, Selvine George MATHIAS, Saara ASIF, Leonid KOVAL, Simon KNOLLMEYER und Daniel GROSSMANN, 2025. Humanizing AI: A Human-Centered Architecture to Developing Trustworthy Intelligent Systems. CS & IT Conference Proceedings. [s. l.]: AIRCC, S. 27-44. ISBN 978-1-923107-57-1. Verfügbar unter: https://www.csitcp.com/abstract/15/158csit03

KNOLLMEYER, Simon, Muhammad Uzair AKMAL, Leonid KOVAL, Saara ASIF, Selvine George MATHIAS und Daniel GROSSMANN, 2024. Document Knowledge Graph to Enhance Question Answering with Retrieval Augmented Generation. In: FACCHINETTI, Tullio, Angelo CENEDESE, Lucia LO BELLO, Stefano VITTURI, Thilo SAUTER und Federico TRAMARIN, Hrsg. 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 979-8-3503-6123-0. Verfügbar unter: https://doi.org/10.1109/ETFA61755.2024.10711054

KOVAL, Leonid, Simon KNOLLMEYER, Selvine George MATHIAS, Saara ASIF, Muhammad Uzair AKMAL, Daniel GROSSMANN und Markus BREGULLA, 2024. Unlocking the Potential of Information Modeling for Root Cause Analysis in a Production Environment: A Comprehensive State-of-the-Art Review Using the Kitchenham Methodology. IEEE Access, 12, 80266-80282. ISSN 2169-3536. Verfügbar unter: https://doi.org/10.1109/ACCESS.2024.3406020

BILAL, Mühenad, Ranadheer PODISHETTI, Leonid KOVAL, Mahmoud A. GAAFAR, Daniel GROSSMANN und Markus BREGULLA, 2024. The Effect of Annotation Quality on Wear Semantic Segmentation by CNN. Sensors, 24(15), 4777. ISSN 1424-8220. Verfügbar unter: https://doi.org/10.3390/s24154777

MATHIAS, Selvine George, Muhammad Uzair AKMAL, Saara ASIF, Leonid KOVAL, Simon KNOLLMEYER und Daniel GROSSMANN, 2024. Pattern Identifications in Transformed Acoustic Signals Using Classification Models. Procedia CIRP, 2024(130), 93-99. ISSN 2212-8271. Verfügbar unter: https://doi.org/10.1016/j.procir.2024.10.061

KOVAL, Leonid, Muhammad Uzair AKMAL, Saara ASIF, Selvine George MATHIAS, Simon KNOLLMEYER und Daniel GROSSMANN, 2024. Addressing the complexity of AI Integration in Manufacturing: A Morphological Analysis. In: FACCHINETTI, Tullio, Angelo CENEDESE, Lucia LO BELLO, Stefano VITTURI, Thilo SAUTER und Federico TRAMARIN, Hrsg. 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 979-8-3503-6123-0. Verfügbar unter: https://doi.org/10.1109/ETFA61755.2024.10711011

ASIF, Saara, Muhammad Uzair AKMAL, Leonid KOVAL, Simon KNOLLMEYER, Selvine George MATHIAS und Daniel GROSSMANN, 2024. Supervised Anomaly Detection for Production Line Images using Data Augmentation and Convolutional Neural Network. In: FACCHINETTI, Tullio, Angelo CENEDESE, Lucia LO BELLO, Stefano VITTURI, Thilo SAUTER und Federico TRAMARIN, Hrsg. 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 979-8-3503-6123-0. Verfügbar unter: https://doi.org/10.1109/ETFA61755.2024.10710718

ASIF, Saara, Muhammad Uzair AKMAL, Leonid KOVAL, Selvine George MATHIAS, Simon KNOLLMEYER und Daniel GROSSMANN, 2024. A Conceptual Framework for Addressing Class Imbalance in Image Data: Challenges and Strategies. In: SGUREV, Vassil, Vladimir JOTSOV, Vincenzo PIURI, Luybka DOUKOVSKA und Radoslav YOSHINOV, Hrsg. 2024 IEEE 12th International Conference on Intelligent Systems (IS): Proceedings. Piscataway: IEEE. ISBN 979-8-3503-5098-2. Verfügbar unter: https://doi.org/10.1109/IS61756.2024.10705251

BILAL, Mühenad, Ranadheer PODISHETTI, Leonid KOVAL, Mahmoud A. GAAFAR, Daniel GROSSMANN und Markus BREGULLA, 2024. Automatized End Mill Wear Inspection Using a Novel Illumination Unit and Convolutional Neural Network. IEEE Access, 12, 124282-124297. ISSN 2169-3536. Verfügbar unter: https://doi.org/10.1109/ACCESS.2024.3454692

KNOLLMEYER, Simon, Oğuz CAYMAZER, Leonid KOVAL, Muhammad Uzair AKMAL, Saara ASIF, Selvine George MATHIAS und Daniel GROSSMANN, 2024. Benchmarking of Retrieval Augmented Generation: A Comprehensive Systematic Literature Review on Evaluation Dimensions, Evaluation Metrics and Datasets. In: GRUENWALD, Le, Elio MASCIARI und Jorge BERNARDINO, Hrsg. Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2024) - Volume 3. Setúbal: SciTePress, S. 137-148. ISBN 978-989-758-716-0. Verfügbar unter: https://doi.org/10.5220/0013065700003838

NOWACKI, Natalie Samanta, Ralph MUELLER, Daniel GROSSMANN und Arndt LUEDER, 2023. Approach for identifying data usage information objects for the later implementation in production environments: Enabling a logic for the information modelling based on use cases using a conversation concept. 2023 The 10th International Conference on Industrial Engineering and Applications (Europe), ICIEA-EU 2023. New York: ACM, S. 169-175. ISBN 978-1-4503-9852-7. Verfügbar unter: https://doi.org/10.1145/3587889.3587915

KNOLLMEYER, Simon, Björn MROSS, Ralph MUELLER und Daniel GROSSMANN, 2023. Ontology based knowledge graph for information and knowledge management in factory planning. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 979-8-3503-3991-8. Verfügbar unter: https://doi.org/10.1109/ETFA54631.2023.10275409

KAMPA, Thomas und Daniel GROSSMANN, 2023. Half&Half: Intra-Flow Load Balancing and High Availability for Edge Cloud-enabled Manufacturing. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 979-8-3503-3991-8. Verfügbar unter: https://doi.org/10.1109/ETFA54631.2023.10275483

KAMPA, Thomas, Amer EL-ANKAH und Daniel GROSSMANN, 2023. High Availability for virtualized Programmable Logic Controllers with Hard Real-Time Requirements on Cloud Infrastructures. In: DÖRKSEN, Helene, Stefano SCANZIO, Jürgen JASPERNEITE, Lukasz WISNIEWSKI, Kim Fung MAN, Thilo SAUTER, Lucia SENO, Henning TRSEK und Valeriy VYATKIN, Hrsg. 2023 IEEE 21st International Conference on Industrial Informatics (INDIN). Piscataway: IEEE. ISBN 978-1-6654-9313-0. Verfügbar unter: https://doi.org/10.1109/INDIN51400.2023.10218014

MATHIAS, Selvine George und Daniel GROSSMANN, 2022. Use Cases of Data Reduction to Time Series Data in Sensor Monitoring. Journal of Ubiquitous Systems and Pervasive Networks, 16(2), 87-92. ISSN 1923-7332. Verfügbar unter: https://doi.org/10.5383/JUSPN.16.02.005

AMBROSY, Niklas, Thomas KAMPA, Ulrich JUMAR und Daniel GROSSMANN, 2022. 5G and DetNet: Towards holistic determinism in industrial networks. 2022 IEEE International Conference on Industrial Technology (ICIT). Piscataway: IEEE. ISBN 978-1-72811-948-9. Verfügbar unter: https://doi.org/10.1109/ICIT48603.2022.10002776

THAKUR, Akshay, Robert BECK, Sanaz MOSTAGHIM, Daniel GROSSMANN und Moritz KUTTLER, 2022. Prediction of Top Key Performance Indicator in Automotive Production System using Data Mining. In: TANG, Loon-Ching, Hrsg. WCSE 2022 Spring Event: Proceedings of 2022 9th International Conference on Industrial Engineering and Applications. Rowland Heights: SCIEI, S. 675-684. ISBN 978-981-18-5852-9. Verfügbar unter: https://doi.org/10.18178/wcse.2022.04.079

MUELLER, Ralph, Daniel GROSSMANN, Sebastian SCHMIED und Ulrich JUMAR, 2022. Co-Simulation im Planungsprozess für die Informationsmodell-basierte virtuelle Inbetriebnahme. at - Automatisierungstechnik, 70(7), 612-622. ISSN 2196-677X. Verfügbar unter: https://doi.org/10.1515/auto-2021-0167

MUELLER, Ralph, Daniel GROSSMANN und Sebastian SCHMIED, 2022. Information model-based virtual commissioning for the testing and co-simulation of real production entities: Enabling of a logic for the virtual commissioning of information models using middleware technologies. IEIM 2022: 2022 The 3rd International Conference on Industrial Engineering and Industrial Management. New York: Association for Computing Machinery, S. 271-276. ISBN 978-1-4503-9569-4. Verfügbar unter: https://doi.org/10.1145/3524338.3524380

MATHIAS, Selvine George, Daniel GROSSMANN, Sebastian SCHMIED und Ralph MUELLER, 2022. Decentralized Integration Approach of Disjoint Modules in Factory Environments. IEIM 2022: 2022 The 3rd International Conference on Industrial Engineering and Industrial Management. New York: ACM, S. 195-199. ISBN 978-1-4503-9569-4. Verfügbar unter: https://doi.org/10.1145/3524338.3524368

KAMPA, Thomas, Christian Klaus MÜLLER und Daniel GROSSMANN, 2022. IP-based Architecture for an Edge Cloud enabled Factory: Concept and Requirements. 2022 IEEE 18th International Conference on Factory Communication Systems (WFCS). Piscataway: IEEE. ISBN 978-1-6654-1086-1. Verfügbar unter: https://doi.org/10.1109/WFCS53837.2022.9779162

MATHIAS, Selvine George, Daniel GROSSMANN und Tapanta BHANJA, 2021. Exploring distance based approaches for reducing sensor data in defect related prognosis. Procedia Computer Science, 2021(184), 614-621. ISSN 1877-0509. Verfügbar unter: https://doi.org/10.1016/j.procs.2021.03.076

SCHMIED, Sebastian, Selvine George MATHIAS, Daniel GROSSMANN und Ulrich JUMAR, 2021. Integration of existing cyber-physical manufacturing systems into a common information model. IFAC-PapersOnLine, 53(2), 10905-10910. ISSN 2405-8963. Verfügbar unter: https://doi.org/10.1016/j.ifacol.2020.12.2827

MATHIAS, Selvine George, Mathew John MANCHA, Daniel GROSSMANN, Bernd KUJAT und Kay SCHIEBOLD, 2021. Investigations on numerical techniques for detecting variations in acoustic emissions. IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society. Piscataway (NJ): IEEE. ISBN 978-1-6654-3554-3. Verfügbar unter: https://doi.org/10.1109/IECON48115.2021.9589074

MUELLER, Ralph, Daniel GROSSMANN, Sebastian SCHMIED und Selvine George MATHIAS, 2021. Architecture of a model in the middle approach for virtual commissioning and integration of production entities. Proceedings: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 978-1-7281-2989-1. Verfügbar unter: https://doi.org/10.1109/ETFA45728.2021.9613619

SCHMIED, Sebastian, Daniel GROSSMANN, Selvine George MATHIAS und Ralph MUELLER, 2021. A concept towards the evolution and versioning of aggregated information models. Proceedings: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 978-1-7281-2989-1. Verfügbar unter: https://doi.org/10.1109/ETFA45728.2021.9613193

SCHMIED, Sebastian, Selvine George MATHIAS, Daniel GROSSMANN, Ralph MUELLER und Ulrich JUMAR, 2021. Information modelling with focus on existing manufacturing systems. Annual Reviews in Control, 2021(51), 392-400. ISSN 1367-5788. Verfügbar unter: https://doi.org/10.1016/j.arcontrol.2021.04.010

MATHIAS, Selvine George und Daniel GROSSMANN, 2021. Efficacy of Statistical Formulations on Acoustic Emission Signals for Tool Wear Predictions. Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL. Setúbal: SciTePress, S. 108-115. ISBN 978-989-758-535-7. Verfügbar unter: https://doi.org/10.5220/0010676400003062

FLEISCHMANN, Albert, Anton FRIEDL, Daniel GROSSMANN und Werner SCHMIDT, 2021. Modeling and implementing of industrie 4.0 scenarios. Modelling to Program. Cham: Springer, S. 90-112. ISBN 978-3-030-72695-9. Verfügbar unter: https://doi.org/10.1007/978-3-030-72696-6_4

VOGT, Anna, Ralph MUELLER, Thomas KAMPA, Rainer STARK und Daniel GROSSMANN, 2021. Concept and architecture for information exchange between digital twins of the product (CPS) and the production system (CPPS). Procedia CIRP, 1292-1297. ISSN 2212-8271. Verfügbar unter: https://doi.org/10.1016/j.procir.2021.11.217

SCHMIED, Sebastian, Daniel GROSSMANN, Selvine George MATHIAS und Ralph MUELLER, 2020. An approach for aggregation and historicization of production entities in the graph. Proceedings 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE, S. 1107-1110. ISBN 978-1-7281-8956-7. Verfügbar unter: https://doi.org/10.1109/ETFA46521.2020.9211907

SCHMIED, Sebastian, Daniel GROSSMANN, Selvine George MATHIAS und Suprateek BANERJEE, 2020. Vertical integration via dynamic aggregation of information in OPC UA. Intelligent Information and Database Systems. Singapur: Springer, S. 204-215. ISBN 978-981-15-3379-2. Verfügbar unter: https://doi.org/10.1007/978-981-15-3380-8_18

MATHIAS, Selvine George, Sebastian SCHMIED und Daniel GROSSMANN, 2020. Monitoring of discrete electrical signals from welding processes using data mining and IIoT approaches. Proceedings, IEEE 32nd International Conference on Tools with Artificial Intelligence, (ICTAI 2020). Piscataway: IEEE, S. 911-916. ISBN 978-1-7281-9228-4. Verfügbar unter: https://doi.org/10.1109/ICTAI50040.2020.00142

SCHMIED, Sebastian, Daniel GROSSMANN, Selvine George MATHIAS und Ralph MUELLER, 2020. An approach for an industrial information model management. Proceedings, 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS). Piscataway: IEEE, S. 402-405. ISBN 978-1-7281-6389-5. Verfügbar unter: https://doi.org/10.1109/ICPS48405.2020.9274751

MATHIAS, Selvine George, Sebastian SCHMIED und Daniel GROSSMANN, 2020. An investigation on database connections in OPC UA applications. Procedia Computer Science, 2020(170), 602-609. ISSN 1877-0509. Verfügbar unter: https://doi.org/10.1016/j.procs.2020.03.132

SCHMIED, Sebastian, Daniel GROSSMANN, Selvine George MATHIAS und Ralph MUELLER, 2020. Integration of manufacturing information via dynamic information model aggregation. Vietnam Journal of Computer Science, 8(2), 245-262. ISSN 2196-8896. Verfügbar unter: https://doi.org/10.1142/S219688882150010X

MUELLER, Ralph, Daniel GROSSMANN, Sebastian SCHMIED und Selvine George MATHIAS, 2020. Validation of dynamic interoperability and virtual commissioning of production equipment in early development stages. Proceedings 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE, S. 1159-1162. ISBN 978-1-7281-8956-7. Verfügbar unter: https://doi.org/10.1109/ETFA46521.2020.9211988

MATHIAS, Selvine George, Sebastian SCHMIED, Daniel GROSSMANN, Ralph MUELLER und Björn MROSS, 2020. A Compliance Testing Structure for Implementation of Industry Standards through OPC UA. Proceedings 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE, S. 1091-1094. ISBN 978-1-7281-8956-7. Verfügbar unter: https://doi.org/10.1109/ETFA46521.2020.9212119

SCHMIED, Sebastian, Daniel GROSSMANN, Ralph MUELLER, Selvine George MATHIAS und Ulrich JUMAR, 2020. Erstellung und Management von Informationsmodellen für bestehende Produktionssysteme. at - Automatisierungstechnik, 68(5), 325-336. ISSN 2196-677X. Verfügbar unter: https://doi.org/10.1515/auto-2020-0021

THAKUR, Akshay, Robert BECK, Sanaz MOSTAGHIM und Daniel GROSSMANN, 2020. Survey into predictive key performance indicator analysis from data mining perspective. Proceedings 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE, S. 476-483. ISBN 978-1-7281-8956-7. Verfügbar unter: https://doi.org/10.1109/ETFA46521.2020.9212111

THAKUR, Akshay, Robert BECK, Sanaz MOSTAGHIM und Daniel GROSSMANN, 2020. Machine Learning for evaluating Kaizens in Volkswagen Production System - An Industrial Case study. Proceedings: 2020 IEEE 7th International Conference on Data Science and Advanced Analytics: DSAA 2020. Piscataway: IEEE, S. 781-782. ISBN 978-1-7281-8206-3. Verfügbar unter: https://doi.org/10.1109/DSAA49011.2020.00114

MATHIAS, Selvine George, Sebastian SCHMIED und Daniel GROSSMANN, 2020. A framework for monitoring multiple databases in industries using OPC UA. Journal of Ambient Intelligence and Humanized Computing, 12(1), 47-56. ISSN 1868-5145. Verfügbar unter: https://doi.org/10.1007/s12652-020-02850-x

DE CAIGNY, Jan, Thomas TAUCHNITZ, Ronny BECKER, Christian DIEDRICH, Tizian SCHRÖDER, Daniel GROSSMANN, Suprateek BANERJEE, Markus GRAUBE und Leon URBAS, 2019. NOA – von Demonstratoren zu Pilotanwendungen: vier Anwendungsfälle der Namur Open Architecture. atp magazin, 61(1), 44-55. ISSN 2190‑4111. Verfügbar unter: https://doi.org/10.17560/atp.v61i1-2.2403

MATHIAS, Selvine George, Daniel GROSSMANN und Gerald Joy SEQUEIRA, 2019. A Comparison of Clustering Measures on Raw Signals of Welding Production Data. Proceedings 2019 International Conference on Deep Learning and Machine Learning in Emerging Applications (Deep-ML). Piscataway: IEEE, S. 55-60. ISBN 978-1-7281-2914-3. Verfügbar unter: https://doi.org/10.1109/Deep-ML.2019.00019

SCHMIED, Sebastian, Daniel GROSSMANN und Bastian DENK, 2019. A systematic top-down information modelling approach for workshop-type manufacturing systems. Proceedings 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE, S. 1305-1308. ISBN 978-1-7281-0303-7. Verfügbar unter: https://doi.org/10.1109/ETFA.2019.8869377

BANERJEE, Suprateek und Daniel GROSSMANN, 2019. OPC UA and Dynamic Web Services - A generic flexible Industrial Communication Approach. ICCAE 2019: Proceedings of the 2019 11th International Conference on Computer and Automation Engineering. New York: ACM, S. 114-117. ISBN 978-1-4503-6287-0. Verfügbar unter: https://doi.org/10.1145/3313991.3313996

NOTHDURFT, Lars, Ulrich EPPLE, Tizian SCHRÖDER, Christian DIEDRICH, Daniel GROSSMANN, Suprateek BANERJEE, Sebastian SCHMIED, Chris Paul IATROU, Markus GRAUBE, Leon URBAS, Tim Peter HENRICHS und Stefan ERBEN, 2018. NOA Demonstratoren Special. atp magazin, 60(1), 44-69. ISSN 2190‑4111. Verfügbar unter: https://doi.org/10.17560/atp.v60i01-02.2348

MIRANDA, Jorge, Jorge CABRAL, Suprateek BANERJEE, Daniel GROSSMANN, Christian FISCHER PEDERSEN und Stefan WAGNER, 2017. Analysis of OPC unified architecture for healthcare applications. ETFA'2017: IEEE 22nd International Conference on Emerging Technologies & Factory Automation. Piscataway: IEEE. ISBN 978-1-5090-6505-9. Verfügbar unter: https://doi.org/10.1109/ETFA.2017.8247771

BANERJEE, Suprateek und Daniel GROSSMANN, 2016. An Electronic Device Description Language based approach for communication with dbms and file system in an industrial automation scenario. ETFA'2016: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA). Piscataway: IEEE. ISBN 978-1-5090-1314-2. Verfügbar unter: https://doi.org/10.1109/ETFA.2016.7733682

GROSSMANN, Daniel, Markus BREGULLA, Suprateek BANERJEE, Dirk SCHULZ und Roland BRAUN, 2014. OPC UA server aggregation — The foundation for an internet of portals. ETFA'2014: 19th IEEE International Conference on Emerging Technologies and Factory Automation. Piscataway: IEEE. ISBN 978-1-4799-4846-8. Verfügbar unter: https://doi.org/10.1109/ETFA.2014.7005354