Signal description and analysis; filtering and estimation synthesis. We develop Digital Signal Processing constrained to its implementation in suitable hardware targets.

Not only classical DSP topologies like frequency selection filters, adaptive filters, Kalman filters, and beam forming. But signal processing schemes which relate classical and modern signal processing techniques.

Data-driven processing techniques employed for Big Data or local in-field processing like fault detection and diagnosis monitors and supervisors.

Identification of performance bottlenecks in fleet management (cars and trucks) or asset management (shop floor and machine tools) using data appropriation and automation of specific messaging networks.

Delivery of results in intuitive dashboards to monitor processes and system’s key performance indices.

Technical systems interact with multiple domains: mechanical, electrical, electronic, chemical, etc. We describe these interactions with power flow techniques and mathematical modeling languages, e.g. Modelica.

We deliver models either as part of our internal processes or as deliverables requested by customers and development partners. This is done by model description and encapsulation into Functional Mock-Up Units.

Realistic simulation is not possible by means of a single simulation tool. Finite Element Models, Signal Flow Models, State Machines and several other forms are brought together by integration efforts disregarding implementation subtleties.

Fully assembled and tested systems is what we deliver. From mechatronic devices to vehicular systems. The method is basically the same, from concept to deployment.

The definition of each electronic components or mechanical part has a traceable reason. The process is applied to systems in multiple criticality categories: mission, safety or even life.