Our (Jan Strohschein, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke, Natalia Moriz & Thomas Bartz-Beielstein) article “Cognitive capabilities for the CAAI in cyber-physical production systems” has been published in The International Journal of Advanced Manufacturing Technology. It is Open Access.
Abstract. This 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.
Cite this article
Strohschein, J., Fischbach, A., Bunte, A. et al. Cognitive capabilities for the CAAI in cyber-physical production systems. Int J Adv Manuf Technol (2021). https://doi.org/10.1007/s00170-021-07248-3
- Received21 December 2020
- Accepted05 May 2021
- Published08 June 2021
- DOIhttps://doi.org/10.1007/s00170-021-07248-3
Keywords
- Cognition
- Industry 4.0
- Big data platform
- Machine learning
- CPPS
- Optimization
- Algorithm selection
- Simulation