Weidmüller Industrial AutoML

Use the power of machine learning without data science skills.

Weidmüller Industrial AutoML

Create and use end-to-end machine learning solutions faster. You only need your application knowledge!

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. ​

Download free whitepaper "Machine Learning automation for industrial applications" here

Your benefits at a glance

Accelerate innovation

Accelerate innovation

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

End-to-End solution

End-to-End solution

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.

Build customer relationships and new business models

Build customer relationships and new business models

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.

Benefit from machine learning without data science skills

Benefit from machine learning without data science skills

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.

Product modules and features

Create, validate and export your own machine learning models with ModelBuilder

This is based on the following step by step approach:

  • Import and explore your machine and process data ​
  • Assess your data based on automatically generated quality indicators (e.g. missing values)
  • Enrich your data by creating custom features
  • Contextualize your data e.g. by defining what's normal behavior and what isn't
  • Choose the kind of machine learning model to create e.g. anomaly detection or classification
  • The tool then automates the model creation process, including feature engineering, required preprocessing and post processing operations
  • Select the most appropriate model from the models created, based on criteria such as model performance and plausibility

Deploy, configure and score your own machine learning models with the ModelRuntime

  • Deploy your models where you need them: on-premise or in the cloud
  • Connect your machine to ModelRuntime by configuring data sources e.g. a database
  • Import the created models and assign them to the specific machine. Multiple models can be used for the same machine
  • Schedule the model execution according to your requirements
  • Visualize results using the embedded GUI
  • Use and configure ModelRuntime programmatically by using the provided interfaces
  • Put model results into actions by importing model outputs into the existing machine or manufacturing systems

Learn more about Weidmüller Industrial AutoML from our experts

Industrial AutoML enables domain experts to create and optimize machine learning models

Industrial AutoML enables domain experts to create and optimize machine learning models

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 speaking with our responsible product manager Dr. Carlos Paiz Gatica.

Industrial AutoML opens up the complex world of Data Science to you

Industrial AutoML opens up the complex world of Data Science to you

Learn more about the data science background of Weidmüller Industrial AutoML by our Data Scientist Dr. Daniel Kress

Learn more about Weidmüller Industrial AutoML in use

Boge Compressors

Boge Compressors

APPLICATION AREA

  • Prediction of the wear behaviour of critical compressor modules

  • Monitoring of compressed air availability

BENEFITS

  • Delivery of the relevant sensor data

  • Optimised production processes and test procedures

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 about the compressor. The model creation process and model selection was intuitive and easy for me to follow.

Dr. rer. nat. Christian Heesing, BOGE

GEA

GEA

APPLICATION AREA

  • Automatic detection of anomalies in the behaviour of separators in the dairy industry

  • Scope: 500 integrated machines

BENEFITS

  • Increase in efficiency and productivity

  • Transfer of application knowledge into an algorithm

  • Extension and development of offered services

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

Matthias Heinrich, Manager Digital Solutions, GEA

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 per cent 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.

Dr. Martin Roth, Data Scientist, MULTIVAC

Der AutoML Modelbuilder ermöglicht eine einfache und schnelle Erstellung sowie Validierung von Verfahren zur Anomaliedetektion auf Basis historischer Daten von Motorströmen eines Fräsprozesses. Die Bedienung ist intuitiv und unterstützt sowohl Anfänger als auch erfahrene Data Science Anwender effektiv.

Andre Schmidt, Automatisierung / Softwareentwicklung, G.Kraft Maschinenbau GmbH

Weidmüller Galvanic

Weidmüller Galvanic

APPLICATION AREA

  • Monitoring of pumps in a galvanic plant

  • Sensors collect data from pumps e.g. vibrations, electrical current, temperature or flow rate
  • Target is to detect unusual pump behavior e.g. a bearing damage to avoid unplanned downtimes and ensure process quality

BENEFITS

  • Easy and quick testing of predictive monitoring of pumps

  • Speed: a model is generated in less than 1 hour with ModelBuilder
  • Intuitive usage: you are taken step by step through the process of model generation
  • Flexible on-premise deployment with ModelRuntime

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