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ENLYZE introduces Python library and API for machine data to enable application development, data science, and AI use cases
From now on, the machine data collected by ENLYZE can not only be consumed from the app: The new interface (API) of the ENLYZE platform and a compatible Python library will allow users to programmatically access machine data in the future.
Synthetic data points that do not occur at the control and are only calculated in the ENLYZE platform are also available for retrieval here.
ENLYZE thus takes a decisive step towards the mission of making machine data easily accessible in companies:
Previously, machine data collected by ENLYZE was only accessible in the ENLYZE app or via OPC-UA in the workshop; the API of the ENLYZE platform now provides the opportunity to use this data in other tools and systems for their own applications:
Process engineers can use the Python library in Jupyter Notebooks to deepen their existing process understanding through data analysis or to accelerate the introduction of new product lines by evaluating experiments.
The open interface can also be used by internal or external developers to create custom, data-centric applications or to enrich existing systems and databases.
Last but not least, the interface can also be used by AI experts to develop neural networks based on machine data - for example, for predictive maintenance.
During audits concerning machine data, the manual and sometimes weeks-long data collection can be reduced to a simple query of the ENLYZE platform.
If you have questions about using the new interface of the ENLYZE platform or about specific use cases, feel free to contact us anytime at hello@enlzye.com.
Three top providers of OEE software in the German-speaking market
Now we want to compare three well-known providers of OEE software and illuminate their strengths and weaknesses. Keep in mind that there is no general "best solution", but rather, depending on requirements, some solutions fit better than others.
Overview
Calculates the OEE from machine data and thus enables more in-depth root cause analyses to improve the OEE.
Calculates the OEE using sensors, without machine data. Therefore, it is quickly ready for use, but no root cause analysis is possible.
Offers comparable OEE functions. However, often associated with extremely long implementation duration and costs.
Strengths
If MPDV Hydra is already being used, no additional software needs to be purchased
Weaknesses
More expensive than a pure OEE tool
No capture of machine data, therefore no possibility for root cause analysis
Tool is limited to OEE calculation
Long implementation times
Often connectivity providers need to be purchased
Restricted OEE functions
No independent configuring and customizing
Become an OEE expert with our OEE series
Here you will learn how to calculate and improve OEE in the long term.
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