mmmake-referenz-sce-vega-grieshaber-kg-ki-sensorkalibrierung
Data Science Services

VEGA Grieshaber KG

Sensor calibration using AI

How AI makes production more efficient? We have demonstrated this to sensor manufacturer VEGA Grieshaber in the field of sensor calibration with the help of machine learning.

The sensor manufacturer and world market leader VEGA Grieshaber KG from the Black Forest develops innovative measuring techniques that are easy to use and offer maximum safety and reliability.

Challenge

Acceleration without loss of quality

VEGA wants to improve its production for the first time with the help of artificial intelligence. To this end, the calibration process for their sensors is to be optimized through the use of machine learning. The aim is to speed up the calibration process without any loss of quality.

Approach

Development of a machine learning algorithm

The AI engineers at mmmake have developed a machine learning algorithm that makes it possible to optimize sensor calibration and save up to 70% of the time required.

A precise two-stage process was used: In the first step, a comprehensive model was extracted that captures the common features of all sensors. In the second step, individual sensors were calibrated to take specific properties into account.

This approach enables customized calibrations for VEGA’s individual customer requirements.

Benefits

Time saving

A time saving of up to 70 % in production with consistently high quality.

Flexibility

A flexible production process enables each sensor to be optimally calibrated according to individual customer requirements.

Efficiency

The time saved enables an increase in production volume without any loss of quality.
Service areas


  • Data Engineering

    Development of customized solutions that improve the data infrastructure.

  • Data Science

    Generating comprehensive insights and added value through the use of advanced analytical techniques.

  • MLOps

    Industrialization of AI projects through continuous model improvements and efficient monitoring.
Technologies

We live technology! Our experts train in a wide variety of areas and are not afraid of new challenges posed by new technologies. Always up to date to offer you the best solution.

In our project with Vega, we relied on neural networks and the development of an individual machine learning algorithm with Python as the programming language. The powerful Tensorflow platform and joblib were used for modeling, which we used for multithreading in order to process the computationally intensive tasks in parallel and thus greatly reduce the overall execution time.

“The solution gives us flexibility and allows us to rethink the calibration process. mmmake impressed us with her holistic way of thinking about the process and transferred lasting knowledge to our specialist area. ”
Jochen Huber Development Team Leader | VEGA Grieshaber KG
mmmake-referenz-sce-vega-grieshaber-kg-ansprechpartner-jochen-huber
Ready for innovation? Ready for innovation?
Ready for innovation? Ready for innovation?
Ready for innovation? Ready for innovation?
Ready for innovation? Ready for innovation?
2023-08-01-MMAKE-Hans-Loefflad-159
Dr. Hans Torben Löfflad
Team Lead AI Engineers Get in touch

What the blog?!

header_abap

Mastering Unit Testing in ABAP: a guide to software quality

Unit testing – an important tool to ensure that your software modules work. We will show you how to proceed.

mmmake-1-jahr-ipai-4

One year at the IPAI

We are celebrating one year at IPAI. In his guest article, our AI expert Hans Torben Löfflad reports on the highlights mmmake has experienced at the IPAI and what you can look forward to in 2024.

mmmake-blog-barrierefreiheit-bitv

Accessibility in Sitecore Forms MVC

Accessibility is not charity! You can find out how to ensure accessibility in Sitecore Forms MVC here.