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How water industry maintenance is benefiting from AI


By Simon Jagers

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In this article

Find out what benefits machine learning algorithms can bring your maintenance strategy within the unique environment of the water industry.

What is one of the most precious and critical resources on the planet? Something that not only gives life to us human beings but pretty much to everything around us. You guessed it right–it’s water.

This makes the water industry, with its rigorous processes of collecting, purifying and distributing fresh drinking water for our use or when released back into nature, an essential part of the modern world economy. But how can you as a maintenance engineer ensure that critical processes keep running round the clock–without disruptive unplanned downtime and emergency equipment rentals? Or go even a step further, and have a maintenance strategy in place that would help you maximize your skills and knowledge, and free up your time to review and maintain those assets that actually need help? Today that is possible with the help of machine learning algorithms and modern condition monitoring technologies. So what is it exactly that makes this combination so effective and scalable?

Sidebar: Critical assets in a water treatment plant

To purify the water of all contaminants and disease-causing agents, hundreds of critical assets within the water treatment plant run non-stop. This includes powerful underground pumps that extract raw water (or sewage), and transport it to the surface and into the plant. Once the water is in the treatment plant, the process of sedimentation, filtration and disinfection start, where dozens of screens, mixers and blowers make sure that all organic and inorganic matter is weeded out. Each of these assets are crucial in maintaining access to clean drinking water (or to ensure water is clean before release into nature), and as such, are vulnerable to failures and breakdown.

Modern condition monitoring techniques can help detect developing faults well in advance. That way your maintenance team can repair or replace an asset during planned downtime, saving costs and the stress of unplanned maintenance. Read here how our condition monitoring technology SAM4 can keep your pumps and blowers running so that you never have to worry about emergency failure or unplanned downtime.

Data, data, data– without disruption

The first superpower of machine learning algorithms is their ability to collect and process asset health data 24 hours a day, 365 days a year. And it doesn’t stop there. Artificial intelligence (AI) also processes that whole spectrum of data, and provides you with actionable insights on the performance of your assets.

It’s always in learning mode

Another superpower of AI is that it’s always adjusting and improving its predictions based on the new data collected. The longer the machine learning system runs, the more data it processes, and the smarter it becomes. It doesn’t wake up on the wrong side of the bed or forget what it learned. It’s always up and running, doing all the heavy lifting, and only alerting the maintenance engineer when there’s an actual anomaly that needs to be reviewed.

Precision is key

One of the most fundamental arguments for the use of machine learning algorithms is their power to detect even the tiniest of changes among a never-ending stream of data. Human beings don’t have the time and ability to go through and analyze the vast amount of information, and spot each variation–but AI can.

Scalable and efficient

These strengths paired with the right condition monitoring system can make your maintenance strategy for a water treatment plant scalable and more efficient. No more wasted hours on routine inspections and replacements–only efficiently spent time on applying your maintenance expertise where it’s needed the most.

But how do you choose the right condition monitoring system?

The best condition monitoring technique and suitability of using AI for your water systems will depend on a range of factors. First, it’s important to know what types of assets you need to monitor. Water treatment plants consist of hundreds of industrial machines that run around the clock: from pumps to centrifuges to mixers. Second, you need to know what failures to detect as each asset fault exhibits itself in a distinct way. Finally, the environment within which sensors will be operating plays a significant role. Will they be monitoring equipment submerged in water with chemicals? That can make or break your final decision on what system to go for.

And there are more considerations to keep in mind. What’s important is that you choose the condition monitoring system that suits your specific configuration. To aid you in this complex decision-making process, we wrote a condition monitoring comparison guide: a detailed guide to five of the most reliable condition monitoring techniques used in water treatment plants and pumping stations. We hope it helps you make the very most out of your water systems’ assets!

The condition monitoring comparison e-book for water systems

Learn how current, voltage, oil, sound, vibration and heat can give you early insight into developing water system failures—and which techniques work best in which situations to keep critical water systems 100% up and running.

This e-book covers:

  • the anatomy of a water system
  • condition monitoring in water systems
  • examples of when different techniques will detect different failures
  • energy and performance insights

Fill in the form to download the e-book.


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