Predictive Dynamic Adsorption
DEC.PDA™
DEC.PDA™ • Predictive Dynamic Algorithm is a sophisticated control strategy integrated into our state-of-the-art SRU™ • Solvent Recovery Units. This algorithm, powered by the DEC.AIP™ • Artificial Intelligence Platform, is transforming traditional gas phase activated carbon solvent recovery by dynamically optimizing processes in real-time, leading to significant cost savings, reduced emissions, and enhanced operational reliability.
The engine driving the DEC.PDA™ is the powerful DEC.AIP™ • Artificial Intelligence Platform. This platform serves as the central nervous system of the SRU™ • solvent recovery, collecting and processing data from a network of sensors. The AI and machine learning (ML) models within the DEC.AIP™ are the key to unlocking predictive control. These models are trained on vast datasets of historical and real-time operational information, allowing them to recognize complex patterns and correlations that would be impossible for a human operator to discern.
The integration of AI/ML through the DEC.AIP™ platform enables the DEC.PDA™ to perform its two primary functions: prediction and dynamic adjustment. By anticipating changes in the process stream, the algorithm can proactively modify SRU™ • solvent recovery parameters, rather than reactively responding to suboptimal conditions.
DEC.PDA™ • key process variables and dynamic adjustments
The DEC.PDA™ focuses on several key process variables to inform its predictive models and subsequent dynamic adjustments. These include:
RH humidity: the presence of moisture in the process air can significantly impact the adsorptive capacity of activated carbon, as water molecules compete with VOCs for adsorption sites. The DEC.RHC™ • Relative Humidity Control module continuously monitors and controls the relative humidity levels. The DEC.PDA™ then uses this data to further refine the regeneration TSA temperature profile and the DEC.PHD™ • Pulse Heat Dehydration process allowing the best in class operation costs;
VOC concentration: the total concentration of Volatile Organic Compounds (VOCs) in the incoming solvent laden air stream is a primary determinant of the required adsorption capacity. Interfaced with the DEC.EMS™ module, the system provides a continuous, real-time measurement of the total VOC load. The DEC.PDA™ algorithm processes this data to predict the carbon bed saturation rate. In response, it dynamically adjusts the adsorption time, shortening the cycle during periods of high concentration to prevent costly VOC breakthrough and lengthening it during periods of lower concentration to maximize carbon bed utilization and avoid the energy waste of regenerating a partially loaded bed;
VOC composition: the specific mix of solvents being treated has a profound impact on the required regeneration parameters. The DEC.GCX™ module automatically samples and analyzes the process stream to determine its precise chemical composition. This detailed data on the identity and relative proportions of each solvent is fed to the DEC.PDA™. The algorithm uses this information to tailor the regeneration TSA (Temperature Swing Adsorption) temperature profile , while providing data to the DEC.SDA™ module. This compositional analysis allows for surgical precision in energy application, ensuring complete desorption while saving theraml energy;
TSA temperature profile: the temperature at which the carbon beds are regenerated is a critical factor in both energy consumption and the long-term health of the activated carbon. The DEC.PDA™ optimizes the TSA temperature profile based on the specific VOCs being recovered and the overall system conditions. For more volatile solvents, a lower regeneration temperature might be sufficient, saving energy. Conversely, for less volatile compounds, a higher temperature profile can be precisely applied to ensure complete desorption.
DEC.PDA™ • benefits
The implementation of the DEC.PDA™ and the overarching DEC.AIP™ platform offers a multitude of advantages for facilities operating Solvent Recovery Units:
Enhanced Efficiency and Cost Savings: by optimizing adsorption times and regeneration energy, the algorithm significantly reduces thermal energy and electricity consumption, leading to the lowest operational expenditures;
Extended Equipment Lifespan: by avoiding unnecessarily high regeneration temperatures and optimizing cycle times, the algorithm reduces thermal stress on the system components (e.g. exchangers, ducts, pipes, valves, etc.), extending their operational life.
Improved Environmental Compliance: the dynamic and predictive nature of the system ensures that VOC emissions are consistently maintained below regulatory limits;
Proactive Maintenance and Reduced Downtime: the DEC.AIP™ platform can also be leveraged for predictive maintenance, identifying potential equipment issues before they lead to costly downtime.
DEC.PDA™ • a paradigm shift
The DEC.PDA™ powered by the DEC.AIP™ platform represents a paradigm shift in SRU™ • solvent recovery technology. By harnessing the power of artificial intelligence and machine learning, DEC is enabling industries to move towards more intelligent, efficient, and sustainable manufacturing processes. This innovative approach not only enhances the bottom line but also reinforces a commitment to environmental stewardship.
Contact DEC!
For more information on DEC's VOC sustainable emission control solutions, powered by DEC.PDA™ • Predictive Dynamic Algorithm, please contact DEC.
