HPC KAESER's SIGMA Air Manager (SAM 2 / SAM 4.0), the next generation master compressed air management system, uses the adaptive 3-D advanced control to make compressed air production and treatment not only faster, but also more efficient and reliable.
3-D advanced control analyses all operating data on an ongoing basis, simulates alternative actions and calculates the perfect compressor combination. The result: Unprecedented energy efficiency. Maintain an overview at all times thanks to easy operation, visualisation and analysis. With secure network technology – conveniently from any PC. Predictive maintenance by Kaeser specialists prevents unplanned downtime.
And if you have big plans for the future: The SAM 2 is ready-designed to accommodate potential compressed air station expansion. A simple software upgrade allows an expansion of the master controller without the need for additional investment in new hardware.
Smart: The SAM 2 / SAM 4.0 not only records switching losses, but also gathers information regarding all dimensions that affect your compressed air station. Using this data, the SAM 2 / SAM 4.0 then calculates the perfect parameters for optimum performance and controls all connected components accordingly.
Secure: Together with the powerful Ethernet-based KAESER SIGMA NETWORK, the SAM 2 forms a future-proof infrastructure that meets all requirements for a highly secure industrial control system.
Efficient: Continuous fine adjustment with a view to achieving optimum energy efficiency (energy management in accordance with ISO 50001) and the option of predictive, demand-oriented maintenance keep life cycle costs to an absolute minimum.
Adaptive 3-D advanced control
The innovative adaptive 3-Dadvanced control not only takes switching losses (start / stops) into account, but also considers additional parameters that influence compressed air system energy efficiency, such as energy consumption due to control losses (idling FC losses) and pressure flexibility.
The adaptive 3-D advanced control ensures optimum efficiency at all times by continuously analysing the relationship between these parameters, predictively calculating the optimum values from various possibilities and by controlling the connected compressors accordingly. The demand pressure provides the foundation for adaptive calculation of switching events and is therefore kept to an absolute minimum