Cargill wanted to spend less money operating their oil boiler while maintaining steam output. Cargill’s internal analyses had yet to significantly impact the boiler’s efficiency because they couldn’t identify the optimal set points to improve boiler efficiency without decreasing steam output.
Braincube built a digital twin of the boiler data. This enabled Cargill to uncover crucial operating parameters. Cargill significantly saved in boiler operating expenses and increased weekly recipe production by 400% after using Braincube for only one year.
Boiler Inefficiencies Result in Loss of Time, Money, and Resources
Cargill wanted to operate their oil boiler more efficiently. The company only used 30% of the oil boiler’s full capacity to produce steam for its operations. Running the machine more efficiently would enable Cargill to spend less money but generate the same amount of steam.
“Our primary goal was to understand the most efficient way we could operate the boiler within the correct capacity,” Herber Souza, Refinery Process Engineer at Cargill, said. “There was a huge opportunity to improve steam production because it is a very expensive part of our operations.”
Cargill tried taking on internal projects to improve efficiencies. Unfortunately, the parameters they identified internally didn’t drastically impact the boiler’s efficiency. Cargill’s high volume of boiler data made it difficult to understand which parameters would improve efficiency.
Understanding the most important operational parameters would empower Cargill employees to make real-time decisions. Providing employees with this autonomy was key to saving the company money, valuable resources, and energy every time they used the boiler.