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Freya Systems

The Center for Business Analytics is pleased to recognize Freya Systems as an honoree of the 2023 Drexel LeBow Analytics 50 Awards. Read more about how Freya Systems used analytics to solve a business challenge.

Submitter

Chris MacNeel, Chief Operations Officer and Senior Data Scientist

Company

Freya Systems

Industry

Information Technology and Systems


Business Challenge

Freya Systems partnered with a local municipal wastewater treatment company to optimize their operations and reduce costs through data-driven tools. The treatment of water consumes a significant amount of energy, and the client’s budget for 2022 was over $28 million — a 5.26 percent increase from the previous year. Wastewater treatment plants, particularly the aeration blower system, consume a substantial portion of energy, accounting for up to 70 percent of energy usage. Freya aimed to enhance efficiency by applying data analytics to optimize the client’s aeration process.

Analytics Solution

Freya analyzed the client’s three years of data, collaborating closely with their team to understand operational intricacies. The data included dissolved oxygen measurements, valve openings, blower activity, pressure, airflow and other relevant parameters. Through analysis, Freya identified frequent, redundant activations of the fourth blower caused by preexisting automated processes. Leveraging this insight, they constructed an advanced random forest algorithm that accurately predicted 30 minutes ahead whether all blowers would be triggered.

Impact

The algorithm’s impact addressed three major challenges in wastewater treatment: cost reduction, greenhouse gas emissions reduction and equipment longevity. The industry’s significant energy consumption results in 45 million tons of greenhouse gas emissions annually. Small-scale improvements can yield substantial benefits. Optimizing operational efficiency and reducing equipment usage prolongs asset lifespan while positively impacting costs and the environment. The algorithm demonstrated remarkable efficacy in predicting simultaneous blower usage during its trial phase, leading to its integration into plant automation. The actual cost reduction is difficult to calculate due to billing structures, but initial calculations revealed that the fourth blower accounted for approximately 10 percent of daily kilowatt usage. With 120 days of concurrent blower usage annually, the algorithm has the potential to save 5 to 8 percent of kilowatt usage on those days. The client reported that Freya’s algorithms exceeded expectations and have successfully integrated into plant automation.