One of the best TV commercials right now is the tax software ad that takes place in a courtroom. The prosecutor’s cleverly crafted closing argument is replaced with the words “Free. Free, free, free, free, free, free. Free.” The defender objects, “Free!” The judge quickly overrules with, “Free… [motions to the prosecutor] free.” With passion, the attorney continues with a rousing string of “free, free, free,” all to the finale of a standing ovation from the spectators and jury.
Can you guess what the company wanted to get across? The tax software—it’s free. That’s it. The marketing agency and company execs knew that the “free” message, a major differentiator and feature for the software’s basic tier, was the key message.
What better way to enhance that message than to double-down, nay, triple-down, to the nth degree?
It feels like the same thing is happening in our industry right now. There is a constant drum of words like: digitalize, intelligent, secure, convergence, open, M2M, scalable, AI and cloud. But in the middle of it all is one singular, convoluted word: smart. Smart this and smart that—but what does that really mean?
With “free,” we know that nothing is truly free. It costs someone something, whether it is the company’s resources or a user’s data.
So it is with smart. Does smart really mean, well, smart? And how smart? Like, fifth grader smart or Ph.D. smart?
To bring some clarity to it all, here are three ways systems and industrial pumps can be smart to varying degrees.
Smart Like a Fifth Grader
For something to be smart, we are assuming that the item’s basic functionality is being intelligently improved in one way or another. A pump’s basic functionality includes turning it on and off, and perhaps modulating its speed.
What I would deem next level (or what I am calling fifth grade status) is to use data directly related to the pump to change the way the pump operates. For instance, say you are running a peristaltic pump and metering the dosage flow of hydrochloric acid into a tank of water. This particular “smart pump” has a fluid contact sensor inside the cavity of the pump above the lubricant level. If the pump hose ruptures, the fluid level inside the cavity begins to increase, triggering the sensor. A signal is sent to the motor telling it to stop, an alarm is sent to the appropriate operators, and the pump is saved from unnecessary damage.
Without this alert, the pump would continue to run, sending lubricant into the line, increased amounts of hydrochloric acid would spill into the environment, the overall process would be starved of resources, energy would be wasted, unnecessary labor spent, damage done, and on and on. I think we would all agree that adding this functionality would be considered smart, both strategically and technically.
The aspect of this elementary scenario that keeps it from being smarter is the element of containment. This solution is certainly a step up from basic functionality, but it lacks in interoperability. Nothing else provides information to, or gets information from, this pump. In other words, the scope of the smart-ness is highly limited. Is it smart? Sure, but not very.
There are many solutions that stop here, whether pumps or otherwise. They are unit-focused on a microscale without taking the next step of working together with a macro perspective.
But apart from falling short, how does this “smart” solution fail? Your hydrochloric pump stopped. Great. But your tank is still being fed water, diluting the mixture, reducing the efficacy of the sprayer below, affecting the quality of the product down the line until the process is manually shut down for repair. Not so great. Usher in the next level of “smarts.”
Smart Like a High School Grad
Industrial automation has been a key component for process control for decades, and for good reason. A computer-controlled system is a great way to visualize the process, keep everything running smoothly and change parameters on the fly. In many ways, the advancements in automation have used the principles of “smarts” as a foundation for as long as they have been around.
Like the popular cloud-based IFTTT (If This Then That) service, you set up rules and they run automatically. You can try this at home with IFTTT by setting up your smart porch light to turn on automatically when your pizza app notifies you that delivery is imminent. (#ProTip—you are welcome.)
What does this have to do with smart pumps? This rule-based approach has been the backbone of industrial automation. If the tank’s level is below 20 percent, then run the pump until the level is 100 percent. If a chemical pump stops, then stop feeding water into the tank, etc.
Relationships and programming can then be added throughout the system to create a string of processes. With the advent of computer-operated machines, robots, high-speed optics and faster computers, industrial automation is making it more possible to increase production speeds, optimize efficiency and reduce relative energy usage.
For pumps incorporated into an automation system, the smart aspect is related to two key components: the level of programming done for the pump (IFTTT) and the amount and kind of information the pump is providing to the system. Perform more programming, the smarter the system and pump operation will be. Provide more information from the pump to the automation system, the more granular process control programming can be.
Often in automation systems, the amount and kind of information available is lacking, and because these are lacking, so are the smarts. Additionally, the programming itself is often limited to binary on/off controls, further limiting the capacity for smarts.
Overall, is industrial automation smart? A resounding, “Yes!” But is it as smart as it could be in this technological age? Not by a long shot.
Smart Like a Ph.D.
Remember those buzzwords from earlier? This is where it starts to get a lot more exciting. The cutting-edge technology that falls under the smart umbrella is where smart gets really smart—and where the future becomes a bit clearer. But first, a review of the components of these graduate-level smart solutions.
In the industrial internet of things (IIoT), industry 4.0 or digital transformation (among many other terms), this higher-level tier of smart incorporates the latest in computing technology, connectivity, data gathering and integration.
For the pump, it takes the concept of industrial automation and doubles down on programming and information.
For example, say there is a series of pumps continually supplying a large arc furnace with huge amounts of water. The only measurements that exist are flow and pump status (on/off). The automation system can call for more flow and engage additional pumps to meet demand. However, there is no knowledge of the pumps’ efficiency, whether they are contributing appropriately to the process, what maintenance issues they are about to experience, and how to process data for insights in an efficient, intuitive way.
Add variable speed drives, and now you can better modulate the pumps based on demand and track the energy being consumed.
Add head and discharge pressure sensors, and now the fluid conditions under which the pump is operating can be known. Add vibration and temperature sensors to the pump and motor, and now cavitation, bad bearings, bent drive rods and high friction can be identified before greater damage takes place. Smart.
But all of this is not particularly useful unless data is being driven into a platform capable of digesting it. The concept of IIoT platforms is a conversation for a different article, but for now, know that the differentiator of platforms is data analytics, which itself is a key part of graduate-level smarts.
Continuing our example above: The pumps supplying water to the furnace are performing their basic functionality, are automated to run according to system demand, and now we have added additional sensors to provide the automation system with additional data.
Now we can add a platform on top to better analyze and visualize the process.
Take the pressure data, flow and motor horsepower, and now it is possible to compare a pump’s performance to the manufacturer’s pump curve. With traditional automation, you may have the data, but there will not be a way to input a pump curve, calculate and plot a point, normalize the points on a single graph, or give a time-based percentage of efficiency. That is graduate-level smarts.
Additionally, you can also autocorrelate time-based data sets to better understand a pump’s operational effect downstream, set up alarms based on calculated values instead of straight parameters and do more efficient peer comparisons between like-pumps. Also, what if you could integrate application programming interfaces, such as weather alerts or vendor part ordering systems, or automate daily reports for maintenance staff with suggested pieces of equipment to keep an eye on?
All of this is possible now with smart systems. That is exciting. It is no wonder the global industrial IIoT market is expected to be almost $1 trillion by 2025.¹
What Is Next for Smart?
As you can see, when talking about smart pumps, we are rarely talking about the pumps themselves. While individual pump features are certainly important, primarily for smarts we must look beyond the pump to sensors, automation, computing location and power, data analytics and interoperability. These are the opportunities where the technological revolution will continue. More sensors and decreased prices are driving the type of data at our disposal. Automation systems are quickly advancing to sustain a true IIoT strategy.
Cloud-based computing and scalability are adding to the flexibility and feasibility of advanced smart systems. Data analytics is driving more informed process strategies and predictive maintenance. And interoperability is becoming more pervasive, opening doors to better equipment integrations.
So if this is now, what is next for smarts? As each of these individual components continue to advance, what do we have to look forward to? Though each deserving their own article, these three smart advances come to mind: 5G, artificial intelligence and digital twins.
5G: This is not just a term for cellphone company marketing departments to use to sell an upgrade. It is a network communication technology that is going to revolutionize the way equipment communicates. Factors like lower latency (1ms) and speeds (10 Gbps) nearly a hundred times faster than 4G are making 5G an unprecedented tool for IIoT.
Artificial Intelligence (AI): While many companies are beginning to offer AI, true AI is still far off. Much like “smart,” there is a spectrum of capabilities under this umbrella term.
But, the excitement behind AI encompasses the ability to more quickly and automatically use data (whether locally or remotely) to come to conclusions, turning troubleshooting into a rare event and capital expenditures into an automated process.
Digital Twins: Once AI becomes mainstream, we will be able to run digital twin simulations—meaning an exact replica of the plant can be run on a computer using the same quirks, environmental nuances and processes unique to a facility.
Want to change the process? Run it in the digital twin and see, with a level of certainty, what the end result will be. This will change the way new equipment is purchased and process materials throughout the facility.
Smart, Smarter & Smartest
Do not get mired down in all the lingo and vague marketing. And do not get short-sighted regarding which equipment is and is not “smart.” Smarts come more from the data being collected, how it is being analyzed and how the findings are being implemented.
The beauty of smart IIoT solutions is that you are not limited to only pumps (or any singular piece of equipment, for that matter).
You can connect and optimize anything, all driving toward predictive maintenance, increased uptime, increased throughput, increased efficiency and decreased headaches. And we can all agree that anything that contributes to these outcomes is, well, smart.