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How An Ethanol Producer Increased Capacity by 12%

Learn how predictive analytics software helps optimize a closed-loop dryer process to meet market demand while reducing energy use and controlling costs.

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Corn generated ethanol biofuel with test tubes on white background

The United States continues to see sustained demand for fuel ethanol as more cities and states adopt policies encouraging or requiring the use of ethanol in gasoline. Dry-grind ethanol production also produces what’s known as distillers dried grains with solubles (DDGS) and wet distillers grains with solubles (WDGS), both of which are in demand as livestock feed.

Thus, what began as a committee of farmers and businesspeople interested in building a value-added ethanol production facility quickly resulted in a full-scale ethanol plant.

The plant is capable of grinding 13 million bushels of corn, producing 35 million gallons of ethanol, and generating more than 170,000 tons of wet and distillers dried grain per year.

The growing markets for ethanol, DDGS and WDGS mean ethanol manufacturers face great pressure to maximize production while controlling costs. The smallest variables in the complex production process can impact yield, time to market, operating costs and profit margin.

As a result, ethanol producers must constantly balance market dynamics with operational efficiencies.

Increasing Capacity

Soon after the plant began operations, the manufacturer began looking for ways to maximize production capacity and efficiency at its dry mill. The team wanted to increase dryer capacity, decrease energy costs, increase DDGS moisture and yield and increase ethanol production through more stable beer column operation.

The beer column is the process where alcohol, water and remaining nonfermentable solids called beer enter the distillation columns used to separate the alcohol from the solids and water mixture. This complex, closed-loop process requires continuous monitoring and control for optimal performance and yield.

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So, the team asked Rockwell Automation to implement FactoryTalk

® Analytics
™ Pavilion8
®, a predictive analytics software, for process optimization. This would allow the ethanol manufacturer to better meet desired business objectives while maintaining regulatory compliance.

Modeling, control, monitoring, analysis, visualization, warehousing and integration capabilities were combined to provide targeted solutions, delivering faster time-to-value and greater cumulative value.

The ethanol manufacturer first worked with Rockwell Automation software engineers to define requirements, clarify expectations and identify anticipated benefits. The project parameters included optimizing the plant’s evaporator, dryer and thermal oxidizer — all key components for beer column operation.

The predictive analytics software optimizes dryer performance by predicting and delivering closed-loop control of moisture. A multivariable, nonlinear controller was used to generate and execute dynamic optimization and control.

Its continuous process control was able to maximize dryer production 24/7 to yield the highest possible returns with the plant’s current equipment configuration.

Graph showing process improvements to ethanol process

By optimizing its closed-loop dryer process using predictive analytics software, an ethanol manufacturer was able to increase production output while reducing energy use and controlling costs. [Click to Enlarge]

The controller was designed to shift the drying load from the dryer to the evaporator. It's also customized to reduce heat losses of the thermal oxidizer, decreasing the need for natural gas.

The software also helps control the thermal oxidizer’s process steam-header pressure and the syrup evaporator, including syrup solids and steam consumption. This allowed for more stable beer column separation using residual evaporator steam.

Rockwell Automation also customized the ethanol manufacturer’s solution to allow for higher average DDGS moisture, which increases DDGS yield.

Increased Production, Reduced Energy

As a result of using this software, the ethanol manufacturer increased production by 12%. The solution also allowed the plant to increase energy efficiency by 9.9%. It also helped minimize standard deviation in dryer moisture by more than 3%.

The ethanol manufacturer obtained these results with minimal additional investment in plant equipment. The team estimates the installation’s total value is more than $2.5 million per year based on industry average marginal values and the cost of natural gas.

 

 

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