Qualifying new processes, machines and components more efficiently. Process adjustments and their effects on multiple parameters, that had been studied and documented in numerous test series so far, are now immediately visible and analyzable.


Full transparency:
Clear visualisation and analysis of all parameters regarding their stability and distribution

Faster qualification:
Automation of analyses and direct derivation of reference models

Process optimization:
Optimization of process parameters with simultaneous freezing of sensor values


Qualification & modifications made easy

Particularly in the production of quality- or safety-critical components, both the introduction and the modification of machines, components or even manufacturing processes involve extremely time-consuming qualification efforts: A large number of tests are carried out, results often analyzed manually, settings changed iteratively, and correlations between influencing factors investigated and documented manually.

Today qualification processes are a burden that need to become more agile
This considerable manual effort is significantly reduced by the Qualification Support application: Automated data acquisition and preparation of the data as digital component twins allow test series to

be performed more quickly, to be documented automatically and their number to be reduced.

Requalifications of existing processes can be performed more often
Even small changes in the manufacturing process, which require a requalification / delta qualification and so far entailed considerable manual effort, can be quickly investigated with this application and effects efficiently checked, released and documented. It is possible, for example, to specify which parameters or measured values should be frozen in order to monitor them online, or to use a component twin of a running machine as the basis for qualifying a new machine.


Offline analysis based on digital twin

The analysis supports the previous process of component, material or process qualification

Build-up of digital twin

Data can be displayed in chronological order, just as it was generated and recorded on the shop floor during manufacturing

Detection of delta qualification needs

The user is informed about areas within the component, where relevant parameters are violated requiring a delta qualification. In combination with the „Online Monitoring“ application, this can also be done automatically

Fine-tuning based on existing machine

Reference twins of well-running machines are selected as a basis and reference for the introduction of new machines

Self-learning model reducing manual effort

To produce the same component on a new machine with considerably less qualification effort, the digital twin can learn from existing machines and support parameter tuning

Loading individual scripts / AI algorithms

Self-created scripts and algorithms can be loaded to optimize qualification according to internal methods

Find out more


Using digital twins for data management and analyses


Digitizing the future of manufacturing

Get in touch.



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