Data analysis / Machine learning

The collection and evaluation of data from products, systems and machines is one of the most important factors of digital transformation. With the help of data-driven decision-making and process optimization, correlations and causes can be determined and future events predicted. In order to achieve the desired future behavior, process parameters can be specifically influenced. Typical questions that can be answered by data analysis include

  • How much demand will I have in the future?
  • How can I plan my processes optimally?
  • How can I monitor my production?
  • How can I detect rejects and anomalies at an early stage?
  • What is the service life until the next maintenance?
  • What errors will occur next?
  • Which parameters must I change in order for my machine to run optimally?

Very different procedures are used to answer these questions. The quality, completeness and consistency of the collected data is crucial for the successful application of data analysis. The use of specific methods strongly depends on the respective application and the available data. The range extends from simple methods, such as linear regression algorithms, to complex methods of machine learning, such as neural networks or deep learning.

Projects we have executed in the areas of reliability analysis, demand forecasting, process optimization, production monitoring, anomaly detection or predictive maintenance have shown that the quality of the collected data and the early involvement of data analysis specialists and process specialists are crucial for the successful implementation of data analysis projects.

Our data analysis team will gladly support you in solving these problems in your company.

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