Technologies & Competences
To solve the most difficult tasks and complex problems, ANDATA relies on a rich portfolio of methods from the fields of system theory and cybernetics.
Today's technical systems - independent of their field of application - are generally characterized by a high level of functionality and complexity. Already the pure amount of functional requirements often makes it very difficult for a systems design engineer to keep pace. Classical, purely analytical methods are usually no longer sufficient for a comprehensive description and modeling of the system behaviour and specification. Development and implementation of complex systems often can only be realized with an extensive use of numerical simulation in combination with methods from the field of Computational Intelligence.
ANDATA's solution strategy combines the concerted and interconnected usage of
- Computational Intelligence and Machine Learning to master high system functionality and complexity,
- Stochastic Simulation for a statistically relevant representation of requirements, data generation of numerical simulations and for robustness management,
- Process Models from software engineering for a strictly requirement-driven process flow.
The Scenario Management bundels these into a concerted mix of methods for the effective development and validation of complex systems.
Advantages & Features
The applied methods are mostly oriented on natural approaches (>natural computation) and are very simple and robust at their core. Nevertheless (or just because of this), complicated, multidisciplinary real world problems can be solved by them in a very pragmatic and integral way. This frees the resources to concentrate on the main engineering problem instead of struggling with the heavy mathematics of the solution techniques.
In contrast to traditional development approaches, the exponential increase in effort can be broken for complex problems. This usually saves enormous development costs and efforts.