[{"status":"public","page":"3513-3532","external_id":{"isi":["000659025000010"]},"year":"2021","author":[{"full_name":"Strohschein, Jan","last_name":"Strohschein","first_name":"Jan"},{"full_name":"Fischbach, Andreas","first_name":"Andreas","last_name":"Fischbach"},{"last_name":"Bunte","first_name":"Andreas","id":"58885","full_name":"Bunte, Andreas"},{"first_name":"Heide","full_name":"Faeskorn-Woyke, Heide","last_name":"Faeskorn-Woyke"},{"full_name":"Moriz, Natalia","first_name":"Natalia","id":"44238","last_name":"Moriz"},{"first_name":"Thomas","full_name":"Bartz-Beielstein, Thomas","last_name":"Bartz-Beielstein"}],"citation":{"ieee":"J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, and T. Bartz-Beielstein, “Cognitive capabilities for the CAAI in cyber-physical production systems,” <i>The International Journal of Advanced Manufacturing Technology</i>, vol. 115, no. 11–12, pp. 3513–3532, 2021, doi: <a href=\"https://doi.org/10.1007/s00170-021-07248-3\">10.1007/s00170-021-07248-3</a>.","ama":"Strohschein J, Fischbach A, Bunte A, Faeskorn-Woyke H, Moriz N, Bartz-Beielstein T. Cognitive capabilities for the CAAI in cyber-physical production systems. <i>The International Journal of Advanced Manufacturing Technology</i>. 2021;115(11-12):3513-3532. doi:<a href=\"https://doi.org/10.1007/s00170-021-07248-3\">10.1007/s00170-021-07248-3</a>","chicago-de":"Strohschein, Jan, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke, Natalia Moriz und Thomas Bartz-Beielstein. 2021. Cognitive capabilities for the CAAI in cyber-physical production systems. <i>The International Journal of Advanced Manufacturing Technology</i> 115, Nr. 11–12: 3513–3532. doi:<a href=\"https://doi.org/10.1007/s00170-021-07248-3\">10.1007/s00170-021-07248-3</a>, .","din1505-2-1":"<span style=\"font-variant:small-caps;\">Strohschein, Jan</span> ; <span style=\"font-variant:small-caps;\">Fischbach, Andreas</span> ; <span style=\"font-variant:small-caps;\">Bunte, Andreas</span> ; <span style=\"font-variant:small-caps;\">Faeskorn-Woyke, Heide</span> ; <span style=\"font-variant:small-caps;\">Moriz, Natalia</span> ; <span style=\"font-variant:small-caps;\">Bartz-Beielstein, Thomas</span>: Cognitive capabilities for the CAAI in cyber-physical production systems. In: <i>The International Journal of Advanced Manufacturing Technology</i> Bd. 115. London [u.a.], Springer  (2021), Nr. 11–12, S. 3513–3532","short":"J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, T. Bartz-Beielstein, The International Journal of Advanced Manufacturing Technology 115 (2021) 3513–3532.","chicago":"Strohschein, Jan, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke, Natalia Moriz, and Thomas Bartz-Beielstein. “Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems.” <i>The International Journal of Advanced Manufacturing Technology</i> 115, no. 11–12 (2021): 3513–32. <a href=\"https://doi.org/10.1007/s00170-021-07248-3\">https://doi.org/10.1007/s00170-021-07248-3</a>.","apa":"Strohschein, J., Fischbach, A., Bunte, A., Faeskorn-Woyke, H., Moriz, N., &#38; Bartz-Beielstein, T. (2021). Cognitive capabilities for the CAAI in cyber-physical production systems. <i>The International Journal of Advanced Manufacturing Technology</i>, <i>115</i>(11–12), 3513–3532. <a href=\"https://doi.org/10.1007/s00170-021-07248-3\">https://doi.org/10.1007/s00170-021-07248-3</a>","havard":"J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, T. Bartz-Beielstein, Cognitive capabilities for the CAAI in cyber-physical production systems, The International Journal of Advanced Manufacturing Technology. 115 (2021) 3513–3532.","mla":"Strohschein, Jan, et al. “Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems.” <i>The International Journal of Advanced Manufacturing Technology</i>, vol. 115, no. 11–12, 2021, pp. 3513–32, <a href=\"https://doi.org/10.1007/s00170-021-07248-3\">https://doi.org/10.1007/s00170-021-07248-3</a>.","bjps":"<b>Strohschein J <i>et al.</i></b> (2021) Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems. <i>The International Journal of Advanced Manufacturing Technology</i> <b>115</b>, 3513–3532.","ufg":"<b>Strohschein, Jan u. a.</b>: Cognitive capabilities for the CAAI in cyber-physical production systems, in: <i>The International Journal of Advanced Manufacturing Technology</i> 115 (2021), H. 11–12,  S. 3513–3532.","van":"Strohschein J, Fischbach A, Bunte A, Faeskorn-Woyke H, Moriz N, Bartz-Beielstein T. Cognitive capabilities for the CAAI in cyber-physical production systems. The International Journal of Advanced Manufacturing Technology. 2021;115(11–12):3513–32."},"volume":115,"title":"Cognitive capabilities for the CAAI in cyber-physical production systems","keyword":["Cognition","Industry 40","Big data platform","Machine learning","CPPS","Optimization","Algorithm selection","Simulation"],"language":[{"iso":"eng"}],"date_updated":"2025-06-26T13:39:22Z","publication":"The International Journal of Advanced Manufacturing Technology","publication_identifier":{"eissn":["1433-3015"],"issn":["0268-3768"]},"date_created":"2025-04-15T13:05:17Z","publisher":"Springer ","abstract":[{"lang":"eng","text":"his paper presents the cognitive module of the Cognitive Architecture for Artificial Intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture is to reduce the implementation effort of artificial intelligence (AI) algorithms in CPPS. Declarative user goals and the provided algorithm-knowledge base allow the dynamic pipeline orchestration and configuration. A big data platform (BDP) instantiates the pipelines and monitors the CPPS performance for further evaluation through the cognitive module. Thus, the cognitive module is able to select feasible and robust configurations for process pipelines in varying use cases. Furthermore, it automatically adapts the models and algorithms based on model quality and resource consumption. The cognitive module also instantiates additional pipelines to evaluate algorithms from different classes on test functions. CAAI relies on well-defined interfaces to enable the integration of additional modules and reduce implementation effort. Finally, an implementation based on Docker, Kubernetes, and Kafka for the virtualization and orchestration of the individual modules and as messaging technology for module communication is used to evaluate a real-world use case."}],"issue":"11-12","department":[{"_id":"DEP5023"}],"publication_status":"published","isi":"1","_id":"12800","doi":"10.1007/s00170-021-07248-3","place":"London [u.a.]","intvolume":"       115","user_id":"83781","type":"scientific_journal_article"},{"publication_status":"published","isi":"1","publisher":"Springer","issue":"1/2","abstract":[{"text":"This paper introduces CAAI, a novel cognitive architecture for artificial intelligence in cyber-physical production systems. The goal of the architecture is to reduce the implementation effort for the usage of artificial intelligence algorithms. The core of the CAAI is a cognitive module that processes the user's declarative goals, selects suitable models and algorithms, and creates a configuration for the execution of a processing pipeline on a big data platform. Constant observation and evaluation against performance criteria assess the performance of pipelines for many and different use cases. Based on these evaluations, the pipelines are automatically adapted if necessary. The modular design with well-defined interfaces enables the reusability and extensibility of pipeline components. A big data platform implements this modular design supported by technologies such as Docker, Kubernetes, and Kafka for virtualization and orchestration of the individual components and their communication. The implementation of the architecture is evaluated using a real-world use case. The prototypic implementation is accessible on GitHub and contains a demonstration.","lang":"eng"}],"department":[{"_id":"DEP5023"}],"intvolume":"       111","user_id":"83781","type":"journal_article","_id":"4518","doi":"10.1007/s00170-020-06094-z","citation":{"ufg":"<b>Fischbach, Andreas u. a.</b>: CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems, in: <i>The International Journal of Advanced Manufacturing Technology</i> 111 (2020), H. 1/2,  S. 609–626.","mla":"Fischbach, Andreas, et al. “CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems.” <i>The International Journal of Advanced Manufacturing Technology</i>, vol. 111, no. 1/2, 2020, pp. 609–26, <a href=\"https://doi.org/10.1007/s00170-020-06094-z\">https://doi.org/10.1007/s00170-020-06094-z</a>.","havard":"A. Fischbach, J. Strohschein, A. Bunte, J. Stork, H. Faeskorn-Woyke, N. Moriz, T. Bartz-Beielstein, CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems, The International Journal of Advanced Manufacturing Technology. 111 (2020) 609–626.","bjps":"<b>Fischbach A <i>et al.</i></b> (2020) CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. <i>The International Journal of Advanced Manufacturing Technology</i> <b>111</b>, 609–626.","van":"Fischbach A, Strohschein J, Bunte A, Stork J, Faeskorn-Woyke H, Moriz N, et al. CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. The International Journal of Advanced Manufacturing Technology. 2020;111(1/2):609–26.","chicago":"Fischbach, Andreas, Jan Strohschein, Andreas Bunte, Jörg Stork, Heide Faeskorn-Woyke, Natalia Moriz, and Thomas Bartz-Beielstein. “CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems.” <i>The International Journal of Advanced Manufacturing Technology</i> 111, no. 1/2 (2020): 609–26. <a href=\"https://doi.org/10.1007/s00170-020-06094-z\">https://doi.org/10.1007/s00170-020-06094-z</a>.","apa":"Fischbach, A., Strohschein, J., Bunte, A., Stork, J., Faeskorn-Woyke, H., Moriz, N., &#38; Bartz-Beielstein, T. (2020). CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. <i>The International Journal of Advanced Manufacturing Technology</i>, <i>111</i>(1/2), 609–626. <a href=\"https://doi.org/10.1007/s00170-020-06094-z\">https://doi.org/10.1007/s00170-020-06094-z</a>","din1505-2-1":"<span style=\"font-variant:small-caps;\">Fischbach, Andreas</span> ; <span style=\"font-variant:small-caps;\">Strohschein, Jan</span> ; <span style=\"font-variant:small-caps;\">Bunte, Andreas</span> ; <span style=\"font-variant:small-caps;\">Stork, Jörg</span> ; <span style=\"font-variant:small-caps;\">Faeskorn-Woyke, Heide</span> ; <span style=\"font-variant:small-caps;\">Moriz, Natalia</span> ; <span style=\"font-variant:small-caps;\">Bartz-Beielstein, Thomas</span>: CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. In: <i>The International Journal of Advanced Manufacturing Technology</i> Bd. 111, Springer (2020), Nr. 1/2, S. 609–626","chicago-de":"Fischbach, Andreas, Jan Strohschein, Andreas Bunte, Jörg Stork, Heide Faeskorn-Woyke, Natalia Moriz und Thomas Bartz-Beielstein. 2020. CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. <i>The International Journal of Advanced Manufacturing Technology</i> 111, Nr. 1/2: 609–626. doi:<a href=\"https://doi.org/10.1007/s00170-020-06094-z\">10.1007/s00170-020-06094-z</a>, .","short":"A. Fischbach, J. Strohschein, A. Bunte, J. Stork, H. Faeskorn-Woyke, N. Moriz, T. Bartz-Beielstein, The International Journal of Advanced Manufacturing Technology 111 (2020) 609–626.","ama":"Fischbach A, Strohschein J, Bunte A, et al. CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. <i>The International Journal of Advanced Manufacturing Technology</i>. 2020;111(1/2):609-626. doi:<a href=\"https://doi.org/10.1007/s00170-020-06094-z\">10.1007/s00170-020-06094-z</a>","ieee":"A. Fischbach <i>et al.</i>, “CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems,” <i>The International Journal of Advanced Manufacturing Technology</i>, vol. 111, no. 1/2, pp. 609–626, 2020, doi: <a href=\"https://doi.org/10.1007/s00170-020-06094-z\">10.1007/s00170-020-06094-z</a>."},"volume":111,"title":"CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems","status":"public","page":"609-626","external_id":{"isi":["000574389900002"]},"year":"2020","author":[{"last_name":"Fischbach","full_name":"Fischbach, Andreas","first_name":"Andreas"},{"full_name":"Strohschein, Jan","last_name":"Strohschein","first_name":"Jan"},{"id":"58885","first_name":"Andreas","full_name":"Bunte, Andreas","last_name":"Bunte"},{"first_name":"Jörg","full_name":"Stork, Jörg","last_name":"Stork"},{"last_name":"Faeskorn-Woyke","first_name":"Heide","full_name":"Faeskorn-Woyke, Heide"},{"last_name":"Moriz","id":"44238","first_name":"Natalia","full_name":"Moriz, Natalia"},{"first_name":"Thomas","full_name":"Bartz-Beielstein, Thomas","last_name":"Bartz-Beielstein"}],"date_updated":"2025-06-26T13:38:24Z","publication":"The International Journal of Advanced Manufacturing Technology","publication_identifier":{"eissn":["1433-3015"],"issn":["0268-3768"]},"date_created":"2021-01-26T12:24:10Z","keyword":["CPPS","Artificial intelligence","Industry 40","Reference architecture","Optimization","SMBO","Cognition","Big data platform","Modularization","AutoML"],"language":[{"iso":"eng"}]},{"isi":"1","publication_status":"published","abstract":[{"text":"Along with the constantly increasing complexity of industrial automation systems, machine learning methods have been widely applied to detecting abnormal states in such systems. Anomaly detection tasks can be treated as one-class classification problems in machine learning. Geometric methods can give an intuitive solution to such problems. In this paper, we propose a new geometric structure, oriented non-convex hulls, to represent decision boundaries used for one-class classification. Based on this geometric structure, a novel boundary based one-class classification algorithm is developed to solve the anomaly detection problem. Compared with traditional boundary-based approaches such as convex hulls based methods and one-class support vector machines, the proposed approach can better reflect the true geometry of target data and needs little effort for parameter tuning. The effectiveness of this approach is evaluated with artificial and real world data sets to solve the anomaly detection problem in Cyber-Physical-Production-Systems (CPPS). The evaluation results also show that the proposed approach has higher generality than the used baseline algorithms.","lang":"eng"}],"department":[{"_id":"DEP5023"}],"publisher":"Elsevier BV","type":"scientific_journal_article","intvolume":"        87","user_id":"83781","doi":"10.1016/j.engappai.2019.103301","article_number":"103301","_id":"12808","place":"Amsterdam [u.a.]","title":"Non-convex hull based anomaly detection in CPPS","volume":87,"citation":{"chicago-de":"Li, Peng und Oliver Niggemann. 2019. Non-convex hull based anomaly detection in CPPS. <i>Engineering Applications of Artificial Intelligence</i> 87. doi:<a href=\"https://doi.org/10.1016/j.engappai.2019.103301\">10.1016/j.engappai.2019.103301</a>, .","din1505-2-1":"<span style=\"font-variant:small-caps;\">Li, Peng</span> ; <span style=\"font-variant:small-caps;\">Niggemann, Oliver</span>: Non-convex hull based anomaly detection in CPPS. In: <i>Engineering Applications of Artificial Intelligence</i> Bd. 87. Amsterdam [u.a.], Elsevier BV (2019)","short":"P. Li, O. Niggemann, Engineering Applications of Artificial Intelligence 87 (2019).","chicago":"Li, Peng, and Oliver Niggemann. “Non-Convex Hull Based Anomaly Detection in CPPS.” <i>Engineering Applications of Artificial Intelligence</i> 87 (2019). <a href=\"https://doi.org/10.1016/j.engappai.2019.103301\">https://doi.org/10.1016/j.engappai.2019.103301</a>.","apa":"Li, P., &#38; Niggemann, O. (2019). Non-convex hull based anomaly detection in CPPS. <i>Engineering Applications of Artificial Intelligence</i>, <i>87</i>, Article 103301. <a href=\"https://doi.org/10.1016/j.engappai.2019.103301\">https://doi.org/10.1016/j.engappai.2019.103301</a>","ieee":"P. Li and O. Niggemann, “Non-convex hull based anomaly detection in CPPS,” <i>Engineering Applications of Artificial Intelligence</i>, vol. 87, Art. no. 103301, 2019, doi: <a href=\"https://doi.org/10.1016/j.engappai.2019.103301\">10.1016/j.engappai.2019.103301</a>.","ufg":"<b>Li, Peng/Niggemann, Oliver</b>: Non-convex hull based anomaly detection in CPPS, in: <i>Engineering Applications of Artificial Intelligence</i> 87 (2019).","havard":"P. Li, O. Niggemann, Non-convex hull based anomaly detection in CPPS, Engineering Applications of Artificial Intelligence. 87 (2019).","bjps":"<b>Li P and Niggemann O</b> (2019) Non-Convex Hull Based Anomaly Detection in CPPS. <i>Engineering Applications of Artificial Intelligence</i> <b>87</b>.","mla":"Li, Peng, and Oliver Niggemann. “Non-Convex Hull Based Anomaly Detection in CPPS.” <i>Engineering Applications of Artificial Intelligence</i>, vol. 87, 103301, 2019, <a href=\"https://doi.org/10.1016/j.engappai.2019.103301\">https://doi.org/10.1016/j.engappai.2019.103301</a>.","van":"Li P, Niggemann O. Non-convex hull based anomaly detection in CPPS. Engineering Applications of Artificial Intelligence. 2019;87.","ama":"Li P, Niggemann O. Non-convex hull based anomaly detection in CPPS. <i>Engineering Applications of Artificial Intelligence</i>. 2019;87. doi:<a href=\"https://doi.org/10.1016/j.engappai.2019.103301\">10.1016/j.engappai.2019.103301</a>"},"external_id":{"isi":["000506715100040"]},"author":[{"first_name":"Peng","full_name":"Li, Peng","last_name":"Li","id":"58937"},{"first_name":"Oliver","full_name":"Niggemann, Oliver","id":"10876","last_name":"Niggemann"}],"year":"2019","status":"public","date_created":"2025-04-16T09:51:12Z","publication":"Engineering Applications of Artificial Intelligence","publication_identifier":{"eissn":["1873-6769"],"issn":["0952-1976"]},"date_updated":"2025-06-26T13:34:10Z","language":[{"iso":"eng"}],"keyword":["One-class classification","n-dimensional oriented non-convex hull","Anomaly detection","CPPS"]}]