By Paul Brake, P.Eng., Dynamic Machine Design
We build big, shiny, fancy control panels with letters and number after their names like NEMA 4X. We then fill them up with wonderful little gadgets and blinking lights, hook them up to doohickeys and thingamajigs all over our equipment. We turn on the power and breathe a sigh of relief that nothing blows up. We press the big green button and voila, we have an automated water treatment plant. Lights are flashing. Pumps are pumping. Filters are filtering. Water is flowing, and somehow we have control of everything that is happening in this magical, mystical wonderland.
And it is quite magical. The more I learn about the science and mathematics that run the Universe, the more magical it seems. When you think of the quantum mechanics and the fluid dynamics that are happening inside your equipment, it is mind boggling that we can get anything right. Yet somehow in the end, we do.
But we can always improve. The question to ask at this point is do we really know what we are actually controlling, and are we controlling and monitoring the right things, at the right times and places? We want to quickly say yes here because we will instantly think of the obvious like effluent pH.
There are a multitude of values that we can measure and a multitude of effects they will have on our process at multiple points in that process. There are values we can measure but are powerless to control. There are values whose levels we can easily affect, but are difficult to measure. There are changes that we can make that will have immediate results, some insignificant, some catastrophic. There are things that we can change that will not show results until hours or days after. Some of those long term results develop momentum; once we start that ball rolling it can be very difficult to rein them back in.
We also tend to allow certain set points to be arbitrarily set by operators. I worked in a smelter once where the operators had tremendous autonomy in how they adjusted the set-points. When shift change came the new operator had to deal with the effects of the previous operator’s actions. The smelter’s output would vary wildly because of it. The same thing can happen in a water treatment system.
You can come on shift and make a change to a set-point, temperature, pump flow rates, alum addition etc. that in the short term may appear to improve your output. That apparent improvement only appears for a short time. The long term my not be so good. For example you can increase temperature and it will enhance your bugs but that will make them process too fast and after a while you will run out of food for the bugs. Not good.
The other thing to remember is where we are taking our readings, and where we are applying controls based on those readings. When we take a reading from a tank, unless that tank is stirred well we will only be getting accurate readings from a localized region. And even if we are stirring well, if we are reading too close to a corner or a protrusion into the tank, or even the wall of the tank, those readings once again may not be representative of the overall system.
Aeration tanks for example will have retention times. We put stuff in one end and take it out at the other. The process condition will thus vary through the tank. Where then to you take measurements of things like dissolved oxygen (DO) or pH? Is your DO for example right above your fine diffusers where the reading will be highest, or along the wall near the bottom where they will be lowest? They will not be the same across the tank. Are you reading levels at the end of process and then applying controls at the beginning? How long does it take before your applied controls are affecting your sensors? Are your controls overshooting your desired set-points? Does your program wait long enough for the changes to be read? Do you have a PID (Proportional-Integral-Derivative) control loop based on that delay? Are your readings good in the beginning of the process but they get nasty further down the tank or in the pipes?
So when we make changes to that system based on our readings, the results may not be positive, may not be immediate, and may not even be readable based on sensor position. I have seen on many systems built where little or no thought was made in the choice of sampling points based on fluid mechanics within the container or on the relative position based on process flow and retention time. People tend to put the sensors were they are most accessible for operations and maintenance staff, not where they best serve the control scenario. So what are you really measuring and what are you really controlling?
Now with automation we tend to believe we are in control. And every system is different. So what I encourage is to limit the variables that can be controlled by the operators once the system is commissioned. I also highly recommend logging those changes so you can back track and see where you went off the tracks. Many but not all are already doing this now. And in your future designs consider the fluid dynamics and process considerations within your tankage and overall system when deciding where to place sensors and where to place controls.
Then there are those items that we simply cannot control. Manual valves are a perfect example. We tend to only automate those things which are absolutely essential for process control. That is quite understandable considering the cost that would be involved in wiring everything into the programmable logic controller (PLC). But we have to remember these uncontrolled variables. We think of valves being opened or closed, but what about valves that are stuck somewhere in between? We can be causing huge changes in process and our PLC could be completely blind to it. It is important not to short change ourselves on sensors trying to be the lowest price on the market.
What are you really controlling? What are you really measuring? What are your fluid dynamic and internal process flow considerations? What are your localized process anomalies? What cannot be controlled? What cannot be properly measured? Incorporate these ideas into your next project.
Image credit: "20130618-RD-LSC-0247," USDAgov © 2013, used under an Attribution 2.0 Generic license: https://creativecommons.org/licenses/by/2.0/