PiT Navigator
Continuous optimisation of complex processes under changing conditions.
Smart process optimisation in real time
Operating complex energy systems safely, stably and with continuous optimisation is the key to energy and cost efficiency, as well as, where applicable, high product quality. PiT Navigator enables the control system to continuously adapt to changing boundary conditions arising from the plant, the environment or the feedstock, thereby keeping the process close to its optimum.
To this end, advanced methods for model-predictive control of complex processes are utilised, in which, amongst other things, data-based process models are used to forecast process behaviour or product quality. In this way, PiT Navigator can anticipate changes and the effects of control actions and adapt the process safely and precisely to the changed boundary conditions.
PiT Indicator
In combustion processes, particularly when dealing with non-homogeneous fuels, valuable information can be gleaned from the flame pattern, especially regarding radiation intensity. If required, PiT Navigator can be combined with additional camera-based sensors for monitoring and analyzing (thermography) the combustion process or the central flame. For monitoring purposes alone, this solution is available as PiT Indicator.
PiT Predictor
In cement and lime production in particular, maintaining defined product properties is of critical importance—laboratory analyses are not typically conducted continuously and involve a time lag. PiT Predictor enables the real-time prediction of product properties (in this case, free lime) based on the current process state and allows for comparison with subsequent laboratory analyses. This saves valuable time, ensuring the expected product quality and enabling timely corrective actions if necessary.
PiT Navigator
Keeping the process well-controlled, with minimal fluctuations and operating close to the possible limits, is the key to efficiency and cost-effectiveness. When fully implemented, PiT Navigator uses corrective actions to precisely control defined actuators, thereby ensuring optimized operation. The system behaves adaptively and, unlike static control technology, can “learn” from the actual process control—whether it involves gradual changes in the plant, new operating conditions, or altered boundary conditions.
