With Weidmüller Industrial AutoML you can optimize operations, increase product quality and create new business models by taking advantage of advanced analytics. As a machine or process expert you can easily build, deploy and operate machine learning models without needing any data science skills. The AutoML tool empowers you to transfer your data and domain knowledge into ML models that generate value for your business. Models can be deployed in existing manufacturing environments to put real time analytics and insights at the fingertips of production workers and stakeholders across your organization.
Benefit from advanced analytics while using your existing machine data and domain knowledge. No extra training required. Build your own machine learning models within minutes.
Create, deploy - on-premise or in the cloud - and operate machine learning models. You can continuously improve model performance easily by retraining models as you gain more insights and collect more data from machines and processes.
Increase customer satisfaction with improved products and services, and achieve a better understanding of your customer’s needs and behavior powered by machine learning technology developed by you.
Watch our 2-minute animation for a compact overview of the Weidmüller Industrial AutoML solution including its key benefits and an explanation on how it works.
Learn more about why machine learning is transforming the industry, how Industrial AutoML is accelerating this process and how you can benefit from it by our responsible product manager Dr. Carlos Paiz Gatica.
Learn more about the data science background of Weidmüller Industrial AutoML by our Data Scientist Dr. Daniel Kress
The Automated Machine Learning Tool helped me to create my own analytics models in a short time without having any data science know-how. I was positively surprised about the good results the tool produced based on my application knowledge from the compressor. The model creation process and model selection was intuitive and easy for me to follow.
We were fascinated by the solution, as we have a lot of process engineers who are very familiar with the machines and who are, to a certain extent, able to interpret the data. With Weidmüller's help, we can now transfer this knowledge to an algorithm
With the help of Weidmüller's AutoML software, we were able to generate an initial model for detecting anomalies with fairly little effort. This has already identified 97 % of the anomalies in the actual process. We especially like how easy the software is to use. The ability to mark normal and abnormal time ranges for model building is very well implemented.
This is based on the following step by step approach: