Why Data Reliability Is Crucial for Treatment Plant Operations

Water and wastewater utilities increasingly rely on data from multiple devices. Effective analysis and reliability help maximize efficiency, safety and compliance.

Why Data Reliability Is Crucial for Treatment Plant Operations
John Fryer

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In years past, operators ran water and wastewater treatment plants based largely on experience, intuition, manual measurements, sights, sounds and smells.
Today, data increasingly drives decisions, often automatically by way of feedback loops through programmable logic controllers, SCADA systems and software. In fact, utility performance and efficiency often rise or fall in direct proportion to the quality of data and its analysis.

John Fryer has worked for more than three decades in the computer, telecommunications and networking industries. Today, he is senior director of industry solutions with Stratus Technologies, a company that specializes in fault-tolerant computer technology — equipment that keeps critical software applications running even if a hardware component fails.

Fryer talked about the importance of data analytics and data reliability in an interview with Treatment Plant Operator.

TPO: Why is it important for water and wastewater utilities to use data and analytics more extensively?

Fryer: Cost pressures are always there. It’s the old story of having to do more with less, being more efficient. On the water side, for example, we have lived through droughts in California and in the Northeast — where I live — for the past two to three years. When it comes to water conservation and detecting leaks in an overall system, the ability to collect data from various points in the network and bring that together and analyze it can be extremely valuable.

TPO: What would be an example of this concept applied to the treatment plant side?

Fryer: A fairly simple example is chemical treatment — making sure you’re adding the correct amount of various chemicals and additives. There are techniques to enable operators to do this automatically on a more real-time basis and get ahead of the curve in making adjustments. If you have the right analytics, you can take a more advanced approach.

TPO: How can utilities manage the increasing volume of data from their systems?

Fryer: Facility managers are looking to add sensory capabilities to pull more data in. Modern control systems collect a great deal more data than systems that are 15 to 20 years old. They may not need all that data to run the control functions day to day, but all the data that gets collected can be very valuable in terms of helping run other parts of the system. But, you need to store that data properly or its value disappears. Data is really a valuable commodity, and the first priority is to make sure it is protected.

TPO: What are some examples of how data can have value beyond its most basic purpose?

Fryer: Consider smart metering on a water system. Instead of having to run around and manually collect the meter data, it comes back automatically to the water department where it’s used to calculate the bills. But they can also use that data to detect anomalous use by customers. Over time, you can build individual customer usage profiles so that, for example, you could detect that Joe Smith is suddenly using a lot more water than normal — maybe he has a leak and doesn’t know it because he’s away on vacation. Or in a drought situation, they could detect when people are using water at 3 o’clock in the morning when they shouldn’t be.

TPO: What other functions can data and analytics serve?

Fryer: Data analytics can help ensure compliance and safety. Events like water contamination and sewage escaping into water sources can be fairly insidious: A problem starts very small and is not detected, and then suddenly people get sick and that’s how you find out. Today, rather than send water samples to a lab and wait to get the results, utilities can automatically collect and analyze samples and store the information in a database. That makes it possible to track parameters as they change over time. The analytics can be set to trigger a point that says, for example, that bacteria have gone above a certain level — one much lower than where it would really cause a problem. It enables operators to be much more proactive.

TPO: Can data analytics be used to improve system maintenance?

Fryer: Yes. In a water and wastewater network, you have mechanical equipment, much of which can be in remote locations. If, for example, a well pump fails, that can have a significant detrimental impact. Today, sensory equipment can be installed on pumps, or modern pumps come with it built in. Temperature, vibration, pressure, flow rates — all these parameters can be put into an analytics engine. The analytics can tell you when you actually need to do maintenance on that equipment. In this way, you optimize resources and time and save money.

TPO: Where does the question of data reliability come in?

Fryer: Many SCADA systems in the field are very old, and when they fail, people have to scramble to get them fixed. Information technology assistance may not be readily available, especially for smaller cities, and they have to go into a manual operation mode until repairs are made. There is no point investing in sophisticated analytics without the back-end infrastructure to support it properly.

TPO: What is the solution to deploying data collection and analytics reliably?

Fryer: The solution is a fault-tolerant computer server. It looks and operates just like a normal server, except that it just doesn’t fail. It provides high availability in a single box — without the need for multiple servers, cables and a storage area network — plus the IT skills to get it all going. It has predictive maintenance capabilities built in. It ensures that all their applications will keep running, while the hardware takes care of itself and keeps all the data they’re collecting. If they are running applications and there is a problem with the hardware, the machine continues to operate in the presence of a failure. The applications are not aware that anything has happened.

TPO: What would you tell to the operators who feel they don’t have the expertise to take care of this kind of system?

Fryer: It’s not a question of what kind of degree an operator has. What’s needed is a system that will reliably run the applications and a reliable partner at the other end of the phone to provide support. It’s a simple matter to train operators to hot-swap parts without having any IT expertise.

TPO: What would you say about the cost of investing in these analytics technologies?

Fryer: It does sound expensive, but the fact is utilities don’t have to do it all at once. For example, a smart metering system can be implemented neighborhood by neighborhood, over time. It’s the same on the predictive maintenance side. They don’t have to deploy a solution across their entire infrastructure. They can pick the most sensitive points in the network, apply technology to that, and see what results come back.



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