Cognitive capabilities for the CAAI in cyber-physical production systems
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 t...
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| Veröffentlicht in: | International journal of advanced manufacturing technology 2021-08, Vol.115 (11-12), p.3513-3532 |
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| container_title | International journal of advanced manufacturing technology |
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| creator | Strohschein, Jan Fischbach, Andreas Bunte, Andreas Faeskorn-Woyke, Heide Moriz, Natalia Bartz-Beielstein, Thomas |
| description | 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. |
| doi_str_mv | 10.1007/s00170-021-07248-3 |
| format | Article |
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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. 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| subjects | Algorithms Artificial intelligence CAE) and Design Computer-Aided Engineering (CAD Configurations Engineering Industrial and Production Engineering Knowledge bases (artificial intelligence) Mechanical Engineering Media Management Modules Original Article Performance evaluation Pipelines |
| title | Cognitive capabilities for the CAAI in cyber-physical production systems |
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