Reduced Costs for Beet Molasses Desugarization Optimization
Discover how Amalgamated Research reduced capital and operating costs for beet molasses desugarization through pilot-scale optimization, presented at the ASSBT 42nd Biennial Meeting. Learn about the critical design parameters and recent advancements in sugar recovery in the USA beet sugar industry.
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REDUCED CAPITAL AND OPERATING COSTS FOR BEET MOLASSES DESUGARIZATION Pilot Scale Optimization Irma Arrieta*, Cy Gaudet, Peter Ferrero Amalgamated Research LLC Presented at the ASSBT 42ndBiennial Meeting March 1st, 2023, Savannah, GA
Background Molasses Desugarization Systems (MDS) is a large-scale chromatographic separation used in the USA beet sugar industry.
Background Molasses Desugarization Systems (MDS) is a large-scale chromatographic separation used in the USA beet sugar industry. Sugar recovery (Z-factor) = sugar in the bag / sugar in the molasses
Background Molasses Desugarization Systems (MDS) is a large-scale chromatographic separation used in the USA beet sugar industry. Sugar recovery (Z-factor) = sugar in the bag / sugar in the molasses above 82%
Background Molasses Desugarization Systems (MDS) is a large-scale chromatographic separation used in the USA beet sugar industry. Sugar recovery (Z-factor) = sugar in the bag / sugar in the molasses above 82% Recent R&D at Amalgamated Research have taken a rigorous approach to the optimization of MDS resulting in reduction of CAPEX and OPEX.
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: column diameter/height, resin volume and number of cells
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: column diameter/height, resin volume and number of cells
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: system capacity (reduced number of cells)
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: system capacity (reduced number of cells) Number of Cells (standard) 8 Number of Cells (optimized) 6 Number of Cells (optimized) 5
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: system capacity (reduced number of cells) Operating Cost: water usage Number of Cells (standard) 8 Number of Cells (optimized) 6 Number of Cells (optimized) 5
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: system capacity (reduced number of cells) Operating Cost: water usage SMB looks to optimize the flowrates in the four SMB zones
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: system capacity (reduced number of cells) Operating Cost: water usage
Defining the Optimization Goal CRITICAL DESIGN PARAMETERS Capital cost: system capacity (reduced number of cells) Operating Cost: water usage SMB looks to optimize the flowrates in the four SMB zones ARi s Optimization Roadmap
Traditional Optimization Roadmap Provide proof of concept information Generate engineering data for scale-up ARi s pilot data can be reliably scaled- up to industrial capacities Consistent performance is maintained
ARis Optimization Roadmap Provide proof of concept information Generate engineering data for scale-up ARi s pilot data can be reliably scaled- up to industrial capacities Generate data to model the separation Model-guided optimization work to generate Performance surfaces Consistent performance is maintained Predict Initial SMB Operating Parameters and provide First Economic Estimations
ARis Optimization Roadmap Provide proof of concept information Generate engineering data for scale-up ARi s pilot data can be reliably scaled- up to industrial capacities Generate data to model the separation Model-guided optimization work to generate Performance surfaces Consistent performance is maintained Predict Initial SMB Operating Parameters and provide First Economic Estimations
Optimization Methodology Change from the traditional approach ARi s optimization work rigorously tests the parameter space We can manipulate the flowrates for each SMB zone to find the optimal operating points
Performance Surface Sucrose Recovery [%] System Capacity [%] Sucrose Purity [%]
Performance Surface Performance Point 95.6% Purity 94.5% Recovery Sucrose Recovery [%] System Capacity [%] Sucrose Purity [%]
Performance Surface Performance Point 95.6% Purity 94.5% Recovery Sucrose Recovery [%] System Capacity [%] Sucrose Purity [%]
Performance Surface Performance Point 95.6% Purity 94.5% Recovery Sucrose Recovery [%] System Capacity [%] Predicted: 23.5% capacity increased Sucrose Purity [%]
Performance Surface Critical Parameters: Sucrose Recovery [%] System Capacity [%] -Capacity increases up to 30% over the standard initial design Sucrose Purity [%]
Performance Surface Critical Parameters: Water consumption [%] Sucrose Recovery [%] -Water usage decreases by 20% of the standard consumption Sucrose Purity [%]
Performance Surface Performance Point 95.6% Purity 94.5% Recovery Water consumption [%] Sucrose Recovery [%] Predicted: 88% of the standard water consumption Sucrose Purity [%]
Performance Surface Performance Point 95.0% Purity 94.5% Recovery Water consumption [%] Sucrose Recovery [%] The surfaces comprises several optimum operating points Predicted: 83% of the standard water consumption Sucrose Purity [%]
Optimization Results Reduced capital costs without reduction in throughput Percentage of Base Case Eight-Cell design Number of Columns 8 - Base Case 6 - Optimized 5 - Optimized Water Sucrose Purity (%) 94 - 95 95.2 93.7 Sucrose Recovery (%) 95 - 97 97.2 94.2 Z60 Consumption 100% 100% 100% Recovery (%) 88 - 89 89.8 84.6
Optimization Results Reduced capital costs without reduction in throughput Percentage of Base Case Eight-Cell design Number of Columns 8 - Base Case 6 - Optimized 5 - Optimized Water Sucrose Purity (%) 94 - 95 95.2 93.7 Sucrose Recovery (%) 95 - 97 97.2 94.2 Z60 Consumption 100% 100% 100% Recovery (%) 88 - 89 89.8 84.6
Optimization Results Reduced capital costs without reduction in throughput Reduced operating costs by decreasing the water usage Percentage of Base Case Eight-Cell design Number of Columns Water Sucrose Purity (%) Sucrose Recovery (%) Z60 Consumption Recovery (%) 8 - Base Case 6 - Optimized 5 - Optimized 100% 80% 80% 94 - 95 95.0 94.0 95 - 97 95.7 91.6 88 - 89 88.1 82.9
Optimization Results Reduced capital costs without reduction in throughput Reduced operating costs by decreasing the water usage Percentage of Base Case Eight-Cell design Number of Columns Water Sucrose Purity (%) Sucrose Recovery (%) Z60 Consumption Recovery (%) 8 - Base Case 6 - Optimized 5 - Optimized 100% 80% 80% 94 - 95 95.0 94.0 95 - 97 95.7 91.6 88 - 89 88.1 82.9
Industrial Implementation A full-scale industrial trial of the optimization results was carried out in 2022.
Industrial Implementation A full-scale industrial trial of the optimization results was carried out in 2022. The capacity of the system was maintained at pre-trial levels. The number of cells used in loop 2 decreased down to six.
Industrial Implementation A full-scale industrial trial of the optimization results was carried out in 2022. The capacity of the system was maintained at pre-trial levels. The number of cells used in loop 2 decreased down to six. Steady performance was observed throughout the trial with decreased water consumption (12% less).
Industrial Implementation A full-scale industrial trial of the optimization results was carried out in 2022. The capacity of the system was maintained at pre-trial levels. The number of cells used in loop 2 decreased down to six. Steady performance was observed throughout the trial with decreased water consumption (12% less). Performance has been maintained after ten months of implementation.
Conclusions Achieved comprehensive view of the performance of a loop 2 separator over a wide range of operating conditions.
Conclusions Achieved comprehensive view of the performance of a loop 2 separator over a wide range of operating conditions. Performance surfaces predict water usage reduction of up to 20%, with a 25% reduction in equipment size (number of cells) and resin cost (for new systems).
Conclusions Achieved comprehensive view of the performance of a loop 2 separator over a wide range of operating conditions. Performance surfaces predict water usage reduction of up to 20%, with a 25% reduction in equipment size (number of cells) and resin cost (for new systems). The optimization goal was fulfilled in terms of minimizing the CAPEX and OPEX of a MDS while achieving the sugar recovery/purity targets.
Conclusions Achieved comprehensive view of the performance of a loop 2 separator over a wide range of operating conditions. Performance surfaces predict water usage reduction of up to 20%, with a 25% reduction in equipment size (number of cells) and resin cost (for new systems). The optimization goal was fulfilled in terms of minimizing the CAPEX and OPEX of a MDS while achieving the sugar recovery/purity targets. ARi offers a turnkey solution for MDS that can accurately predict and locate economic optima.
Conclusions Achieved comprehensive view of the performance of a loop 2 separator over a wide range of operating conditions. Performance surfaces predict water usage reduction of up to 20%, with a 25% reduction in equipment size (number of cells) and resin cost (for new systems). The optimization goal was fulfilled in terms of minimizing the CAPEX and OPEX of a MDS while achieving the sugar recovery/purity targets. ARi offers a turnkey solution for MDS that can accurately predict and locate economic optima. ARi srigorous optimization process is not limited to MDS but it s applicable to other industries.
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