[ Webinar Recap ] Advanced Analytics for Water & Wastewater Treatment
Advanced analytics is not new to many industrial manufacturing industries. The Oil & Gas and Chemicals industries have been using analytics for years to gain insights into their operations. Recently, especially given the interruptions due to COVID-19, many companies within other manufacturing industries have understood that it is essential for them to have more business insights from the data their plants are actually collecting. For example, they need to leverage the data their plant historians have collected for years or even decades. And this is true for the Water Industry.
Advanced analytics platforms can provide significant value to the Water and Wastewater sector and its plant managers and process experts tasked with running treatment facilities by helping them to easily tackle common challenges and complex optimization problems and improve asset performance. It provides substantial value by also aiding in energy reduction, knowledge exchange, maintenance costs, regulatory compliance, data availability, and analytics expertise.
The Promises of Advanced Analytics
Not only can an advanced analytics tool help the Water Industry solve process issues, but it can also provide substantial improvement potential:
- Improve your maintenance schedule to reduce maintenance costs and save energy consumption.
- Monitor your pump performance to prevent pump failure and ensure smooth plant operations.
- Automate your findings into early warnings to reduce costs and avoid nitrogen/carbon emission.
- Increase your knowledge sharing resulting in more solved cases and employee efficiency.
- Ensure your data availability by preventing data silos.
- Solve your day-to-day questions without the help of data scientists.
It can also help plant managers and process experts realize additional improvement projects that they might have found on their own.
Now onto the How…
Use Cases from the Webinar
In our recent webinar, “Advanced Analytics for Water & Wastewater Treatment”, TrendMiner Data Analytics Engineer Daniel Münchrath demonstrates how our self-service analytics is being used to optimize Water Industry processes.
Use Case 1: Monitoring Pump Performance
Plant managers and process engineers take note. This use case is based on finding the desired operation zone of the sewage pump and shows how TrendMiner allows process experts to monitor their assets to schedule maintenance at the right time.
With our software, process experts can:
- reduce equipment cost
- reduce downtime
- avoid unwanted process states
To see Daniel demonstrate this, register for our webinar on demand watch it at the 22:22 marker.
Use Case 2: Aeration Elements
The aeration elements in the biological wastewater treatment suffer from fouling effects which leads to decreased oxygen concentration and decreased nitrogen/carbon conversion rates. This use case shows how TrendMiner can be used to create a clear overview of the oxygen concentration within the plant and how plant managers, engineers. and operators can use the achieved situational awareness to schedule the maintenance/cleaning process in time.
These benefits are substantial:
- improved regulatory compliance
- reduced energy cost
- improved maintenance schedule
To find out how to increase energy efficiency with improved maintenance scheduling, check out the webinar on demand at time stamp 33:39.
“Right after the start of COVID-19 lockdown TrendMiner clearly showed a change in the early morning peak of wastewater to our sewage treatment plant…This tool gives great insights of the performance in our plants and helps our engineers find areas for performance improvements.”
Do Your Job Faster, Better, Smarter
As demonstrated in the webinar, TrendMiner’s platform allows those of you in the water industry, or working with water and wastewater assets, to be able to:
- visualize data
- use its search algorithm and pattern recognition to gain process behavior insights
- find root causes
- set process monitors and alarms to alert process experts about potential deviations so they have time for corrective actions
- make predictions about future process behavior
- incorporate process contextual information, so the entire team has a better understanding of operations