Backes combines process engineering, data analytics and automation into intelligent systems for gas-fired industrial furnaces, wastewater and biogas plants, and backwash filters – based on existing measurement data and focused on real plant operation.
Modern plants continuously record temperatures, pressures, flow rates, energy consumption and operating states. The decisive value emerges only when these signals are evaluated together and in their time-based process context.
We connect measurement data across signals, time periods and operating states. The result is a robust digital understanding of the process – a basis for faster root-cause analysis, targeted optimization and predictive control decisions.
Our solutions combine multidimensional data analysis, digital process models and model-based control. The entry point is pragmatic; the expansion stage can extend to continuous integration into existing automation systems.
Gas, air, furnace pressure, exhaust gas and cycle timing act as a coupled system. We identify dynamic loss windows and develop robust strategies for energy efficiency, process stability and reproducible quality.
A continuously reconciled process model makes delayed gas formation more plannable. This allows gas storage, pressure control, heat input and CHP output to be coordinated more predictively.
Backes develops its own control and process concepts for plants where dynamics, interactions and technical limits determine economic operation. Patent applications have been filed with the DPMA for all three solution areas.
Modern computing power makes it possible to evaluate many signals, time courses and operating states simultaneously. This creates transparent models, robust forecasts and control decisions that reflect the real process.
The project scope is tailored to the plant – from a focused potential check to step-by-step integration of model-based control with traceable proof of effectiveness.
Assess signals, quality, time reference and relevant operating states.
Identify loss windows, influencing factors and economically relevant levers.
Validate KPIs, models and measures with real operating data.
Implement integration, fallback level, monitoring and proof of effectiveness in a structured way.
In an initial technical discussion, we assess objectives, data availability and a sensible pilot scope – specific, non-binding and related to your plant.
