Make your machines smart

Make your machines smart

The Industrial Analytics offering from Weidmüller stands for application-oriented AI applications to help you detect and classify anomalies, thereby effectively reducing downtimes. Through predictive maintenance, you can plan service intervals in a targeted manner as and when required. What’s more, you can make reliable predictions with regard to the quality of your products (predictive quality), based on seamless recordings of sensor, condition and process data.

You decide whether you want to work with our experienced data scientists and jointly design solutions or whether you want to use the Automated Machine Learning Tool to independently exploit the advantages of artificial intelligence.

Your benefits at a glance

Local or in the cloud

Local or in the cloud

100% security for your data. With our cross-platform Industrial Analytics solutions, you can decide for yourself how you want to use your data. Our services work on all standard cloud solutions, such as Microsoft Azure, Amazon Web Services and IBM Cloud. They can also be used "on premises" on internal servers or directly on the machine.

Strong partner with industrial expertise

Strong partner with industrial expertise

Thanks to our many years of experience in the field of machine construction, we know your applications inside out and we know that the decisions you make today will continue to affect you for many years to come. That's why we have assigned ourselves the task of developing solutions that we can continually improve upon and develop together with our customers.

Complete solutions from a single source

Complete solutions from a single source

We will help you to design an optimal data infrastructure and to select the perfect sensors and components. Our analytics modules are tailored to your use cases in order to adapt the computing capacity and data transmission in line with your existing IT environments.

Industrial IoT platform for data-based services

Are you faced with the challenge of expanding your high-margin service and aftermarket business in order to strengthen, expand, or defend your competitive position against new players? An important requirement for this is the networking of machines and the analysis of the data to be in a position to offer these services.

The Weidmüller Industrial IoT platform supports this and offers fast and targeted access to machine data on a cloud based software architecture.

Your special advantages
  • Simple implementation of end-to-end solutions from a single source
  • Customised solution for the optimal implementation of business processes and services
  • Protection of investments thanks to maximum transparency - e.g. through service levels that can be called up at any time
  • An optimal basis for new services including Industrial Analytics

Automated machine learning: Become a pro yourself

Developing industrial analytics solutions usually requires the specific know-how of a data scientist. Our Automated Machine Learning tool allows you to use AI and ML-based models independently, without the need for external support. It enables you to generate models that can recognise the normal and erroneous behaviour ofyour machines based on your own data and application know-how. The platform independent software helps you to do this with automated model generation and a simple user interface.

Your special advantages
  • Based on your own data and expert knowledge
  • Without the need for external consulting or a data scientist
  • Automatic generation of models
  • Simpler and faster solution development process
  • Visualisation of machine data
  • Independent training of the software to detect normal operation and malfunction of the machine
  • Platform-neutral
  • Independent continuous optimisation of the models
Thanks to the technical and methodical competence, the good cooperation and the commitment in the proof of concept, we were able to quickly and easily identify the potential of the existing data. Based on the first evaluations, we were already able to implement improvements in our process.

Daniel Hanebrink, Industrial Engineering, Miele & Cie. KG


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