Knowledge extraction in catalysis utilizing design of experiments and machine learning

2022 ◽  
Vol 36 ◽  
pp. 100781
Author(s):  
Blake MacQueen ◽  
Rasika Jayarathna ◽  
Jochen Lauterbach
Author(s):  
Stefan Windmann ◽  
Christian Kühnert

AbstractIn this paper, a new information model for machine learning applications is introduced, which allows for a consistent acquisition and semantic annotation of process data, structural information and domain knowledge from industrial productions systems. The proposed information model is based on Industry 4.0 components and IEC 61360 component descriptions. To model sensor data, components of the OGC SensorThings model such as data streams and observations have been incorporated in this approach. Machine learning models can be integrated into the information model in terms of existing model serving frameworks like PMML or Tensorflowgraph. Based on the proposed information model, a tool chain for automatic knowledge extraction is introduced and the automatic classification of unstructured text is investigated as a particular application case for the proposed tool chain.


ACS Nano ◽  
2018 ◽  
Vol 12 (8) ◽  
pp. 7434-7444 ◽  
Author(s):  
Bing Cao ◽  
Lawrence A. Adutwum ◽  
Anton O. Oliynyk ◽  
Erik J. Luber ◽  
Brian C. Olsen ◽  
...  

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