Beyond automation: Humans as process controllers
Peter Martin, PhD, is vice president, business value solutions for Invensys Operations Management. He has emerged as something of a control strategy futurist, looking for how our concepts of process control need to evolve as business-related demands on manufacturing change. Control Engineering contributors Vance VanDoren and Peter Welander asked the questions.
CE: Over the last year or two, you have made comments about how process industries are changing, and suggested that you expect a larger role for humans in control functions. With the growing importance of automation, this seems counter-intuitive. Where do you see this headed?
What we see going on is that automatic control (and manual control) have been applied to controlling the efficiency of plants for many, many years. It’s been going on for a long time, and we’re pretty good at it. Over the years, we’ve been able to replace human decisions with automatic decisions, especially in a more real-time world where automatic controls can make decisions much better, more effectively, and more quickly. I don’t see a reversal of that. What I do see going on is that the critical business variables in these plants are starting to change in real time. So, for example, 15 years ago, companies used to be able to develop contracts with their electricity suppliers for a year at a time, essentially relegating the price of electricity to a constant for the contract period. With the price as a constant, all you really needed to control was consumption, and by reducing consumption, it directly translated into profitability. With the opening of the power grid and deregulation, all of a sudden the price, not only the usage of electricity, but the price is changing more frequently than it ever has. In fact in the U.S., on the open market, the price changes about every 15 minutes.
Historically, we’ve applied control theory to the plant floor, and we’ve applied management theory to the business. That made some sense because all of the critical business variables didn’t change within a given month. You could use monthly information from SAP or Oracle, and you’d be getting measures of energy costs, material costs, and product value, all of those things that were fairly stable and could be managed with monthly data. Today with the opening of the power grid and the domino effect that it’s caused, all of a sudden we’re seeing not just electricity costs, but the price for natural gas changes every 15 minutes. Similar things are happening to some of the materials used in production process, especially heavy process industries. If you watch the price of critical metals like copper, they might change multiple times per minute. If one of those is a raw material in your manufacturing process, that’s a new dynamic introduced to your manufacturing process—a high-speed change that’s never been there before. And if you’re going to play that correctly, perhaps the products that are being produced should be adjusted to reflect that and reflect market demand. The three critical business variables—production value, energy costs, and material costs—are changing multiple times daily, and companies are still trying to manage them. It’s not that I see a lessening of applying control theory on the plant floor, but rather I see controlling the business side of industry as more of a real time control problem than it’s ever been, and we believe that we have to apply real time control theory to those critical business variables.
That said, it’s not easy to apply something like PID control because you don’t get the natural periods of the loops in the business side that you get in the process side. Therefore, what we see going on is that humans have to jump in and be controllers of the critical profitability variable almost in the same way they were 100 years ago for the process variables. Back then we set operators on a hand valve looking at a gage, and we said to the operator, “Look, when the needle goes this way, turn the valve this way, and when the needle goes the other way, turn the valve the other way.” We used humans as controllers. The interesting thing about it is that humans did a pretty good job. What I see going on, in terms of control theory, is that humans are getting involved more in controlling profit. A lot of people think, “You’re talking about business managers.” But no, I’m talking about operators and maintenance people. When an operator changes the set point of a loop, let’s say a temperature loop from 400 to 410 degrees, from a business point of view, that either added value or destroyed value. There’s no other alternative. That type of change is either creating or destroying economic value. Just like in the old days of manual process control, if we can stick operators in front of a gage that will show them what the impact is, in terms of the business, of every activity and action they take, then over time the operators can learn how to take actions and how to perform activities that will drive the most value. That’s where I see much more manual control than we would have seen 10 years ago, but not at the process level, it’s at the business level. But it’s the same people—it’s the operators or the maintenance people learning how their actions and activities impact the profitability of the plant. In reality, that is feedback control.
It’s the difference between control and management. Management is when you can’t control something. If you can control it, do. If you can’t control it, manage it. We’re getting to the point in business where the traditional management constructs, like using monthly reports to manage your business, are truly becoming obsolete. It’s not that we don’t need the monthly reports, but you can’t use that same monthly data to manage the performance of your operations, because the operations are moving so fast that the speed of the business precludes running it monthly. So if you can’t run it monthly, you have to run it in the time frame in which it changes, which is essentially becoming real time. Then the people that become the business managers, who are the manual controllers of profitability, are the operators, maintenance people, supervisors, and engineers.
CE: But won’t all these parameters taken together threaten to exceed the ability of human operators to keep up? Won’t we have to develop some kind of automatic control at the management level just the way we did in the 1930s at the process level?
I absolutely think that is going to have to happen. That’s the bad news. We all need to be looking for how to do automatic control of all these variables. Unfortunately, it’s not as simple as applying PID. We have to be looking for that automatic control algorithm. The good news is that in most parts of the world, governments have jumped in and regulated the time in which these variables can change. For example, if you look at the price of electricity on the open grid, in the U.S., it changes every 15 minutes. That interval is not because of any business or physical reality but because the government says, “You can’t change any faster because we can’t keep up with it.”
When we first started looking at this, everybody said, “Yes, this can happen for energy, but it’s never going to happen for raw materials because people have too much inventory, and the inventory itself will slow things down.” That tends to be true. The inventory does add a capacity buffer effect, but what I’m seeing going on right now is business managers who understand what’s going on have two dynamic problems: One is controlling the business, the second is controlling the physical process. We see a lot of people rethinking the physical processes themselves.
North West Redwater Partnership is building a new refinery near Edmonton. We haven’t built a new refinery in North America in decades, so why are they doing that? Today, when you produce crude from the oil sands in the Athabasca range, you put it in a pipeline and pump it down to the U.S. or wherever you’re shipping it to be refined. During that trip it ends up being in the pipeline for three days, and during that period the price of that crude may have changed 120 times, and there’s not a thing a business manager can do about it. What we see going on is that the whole concept around storage and inventory has to be altered along with the whole trend. I was at a Momentive Chemical plant in Deer Park, Texas, recently, and it’s fascinating: they have no on-site storage. They buy their raw material off a pipeline from the refinery next door. All of a sudden we’re finding more and more processes that are changing because the real-timeness of these variables. Everything is going to become faster and faster.
I think we’re starting a new era for control engineers where they’re going to have to look at this problem and figure out how we can do predictive control or model-based control of business variables. You’ll have profit control cascading to efficiency control, and we’ll have a new type of closed-loop controller. There are some really fun challenges.
CE: The tricky part will be finding the right control algorithm.
You can’t use PID because you don’t have a natural period in the business variable loop. We’ve come up with model-based control and other things that are really pretty sophisticated. Maybe some of these other algorithms, expert algorithms, or neural-net models may make some sense going forward. Down on the plant floor, you can always default to PID, and we do, because it’s relatively easy and effective. Maybe when we get up to business control, because you can’t default to PID, we might see some of the great research that’s been done over the last couple of decades show its applicability with business variables rather than process variables.
One way might be to look at it as a real-time optimization problem of sorts, where you’re trying to balance production value, energy cost, and material costs that are constrained by safety and environmental considerations. The problem with linear or non-linear programming today is that you typically have to pick an objective function and relegate all your other objectives to constraint functions. I’m not sure that will be dynamic enough. There is some new work being done in multi-objective linear programming and optimization that I think holds a lot of promise. You’re trying to balance three objectives, production value with energy cost and material cost, so that may be the direction for closed-loop business control.
CE: It will have to be some sort of iterative search optimization. There’s not going to be a neat tenth-order differential equation that relates inputs to outputs, which is the fundamental premise of virtually all regulatory control.
The other issue when you start to look at multiple-objective control and optimization is historically, linear and non-linear programming with multiple constraint functions requires a lot of computing power to process things and come up with optimal settings. As the time gets shorter and shorter, how do you get that amount of computing power in a cost-effective way? If you think about it, there are some really fun challenges. I think the golden age of the control engineer is almost upon us.
CE: I think the golden age will be when we can start to use some of these new techniques to control our processes, instead of following tradition and returning to PID as we have for the last 60 years.
The thing that I worry about, and I’m speaking in large generalities here, is if it truly is a cascade control structure, and we cascade profitability to efficiency, we have to remember the old concept that the secondary loop of a cascade controller has to be four times faster than the primary loop. As the business variables get faster and faster, we may find PID control of the process becoming a constraint. The process could become chaotic if the business variables move faster than the periods of the loops on the plant floor. That will be a fascinating thing. If that starts happening, we’ll have no choice but to look at other methods of control.
CE: That’s a natural extrapolation, but thinking in terms of costs and business variables changing faster than flow or pressure blows the mind.
Put on a ticker for commodity prices some time. When you see the price of copper changing every 32 seconds, can you control a temperature loop much faster than that? So ask yourself, why don’t we have a control problem right now, because some of these variables have gotten themselves to the speed where they’re actually breaking into the classical temperature and level domain, if not the flow and pressure domain. The issue ends up being that instead of worrying about the problem, we’re ignoring it and we buy our raw stock in bulk so the inventory gives us the buffering. We just don’t worry about it.
Where it will all blow up, I believe, is when some business realizes that it can have a huge competitive advantage by playing the price of its raw materials effectively. When that one company does it, everybody else is going to say, “Wait a second, in order for us to survive in this environment, we have to think differently.” I don’t think we’re far, time-wise, from that happening when I see sites like Momentive Chemical in Deer Park. No on-site inventory combined with real-time acquisition and distribution of product via pipeline. It fascinates me. Huge amounts of money are at stake.
CE: This sounds interesting, but as a practical matter, how much leeway will, or can an operator have to change what’s happening? If the plant is in a sold-out state and the objective is to create as much product as possible, when does it become practical to start trying to fine-tune the parameters?
We have to look at the dynamics of the process itself, but I think the decision criteria could get complicated and it may be impractical if the dynamics of the physical process are slower than the business process. That could get into some very difficult things.
The issue is this: We’ve been working in a world of sold-out everything. The primary philosophy of business has been to make as much as you can in a given period of time, and life as we know it is good. That’s what everybody has been doing. The best example is the power industry. For years, the way the power industry worked was they had central station, coal-fired power plants that made as much power as they could 24/7. Pricing was regulated so they always made a profit, everything was good, and nobody could imagine anything different.
Then what happened? They deregulated and the grid opened up. That means all of a sudden there were, by law, other power suppliers, such as windmills, photoelectric, and co-gen plants, all these sources of power, which if they wanted to send power onto the open grid, they had to be paid money, based on the current value of electricity on the grid. You went from a situation where you had a single producer producing for a series of users, to where you had multiple producers producing for multiple users, and the supply side is going up and down at a higher rate than anybody had seen it go up and down. You might have a co-gen operation at your plant, and for the next three hours you don’t need its output yourselves in the plant, so you put it out on the grid. Now the supply of electricity goes up and people have to adjust. That’s what the smart grid is all about. We’re in a brand new dynamic environment, which is also fascinating because you can’t store power. So with no inventory buffer, what’s going on? You’ve got real-time strategy—we actually had to go to a new structure of the generators, the producers, the grid managers, and the consumers. All of a sudden you have a very dynamic environment. So what did the energy producers have to do? They built new types of plants. Combined cycle plants that could start up and shut down quickly, because if there was a demand on the grid, and the big energy companies couldn’t provide enough power to meet the demand, they were penalized, so they had to have those combined cycle plants start up. Those plants produce energy at much higher cost than the coal-fired plants, so all of a sudden you see these big swings in price. In response to that, even at the home level, we’re going to see things like thermostats that read not just the temperature, but the current price of electricity. You’ll put wet clothes in the dryer in the morning, and it will turn itself on when it sees that the price of electricity is low enough.
The power industry is an extreme, but it’s where all industrial operations are going. Trucks, trains, and material in pipelines don’t travel as fast as electricity, but the dynamics of these systems are going to drive a true reconstruction of how we manufacture. I can picture in the future, where instead of building mega-scale Texas City refineries, we start building smaller refineries that can be more agile, just like the combined cycle plants in the power industries. Hydrocarbon companies won’t run a plant at a time; they’re going to be running their asset set across the entire value chain because if the price of crude is too high right now, so that I make gasoline at a loss, I should slow down production, even if I’m in a sold-out condition. If you can’t play that game, you’re going to lose money during these difficult periods. They are already hitting the power industry, and they’re going to hit the rest of our industries. The ones that can play that game are going to be profitable, and the other guys are going to be out of business. I believe this is where it’s going.
The day of the mega-scale coal-fired power plant is behind us. The day of the mega-scale refinery may be behind us. Maybe our manufacturing philosophy has to change. Maybe we have to go to more localized micro-manufacturing in order to match the dynamics of the market place. Those are the kinds of things that we’re going to have to start thinking about. As an industry, we came up in the era where everything was sold-out, all you had to do was make as much as you can, and margins were huge. That time is behind us. Now, margins aren’t huge and everything isn’t sold out. Some times of the day we’re making money, and other times of the day we’re losing money. The world has changed, and it’s going to require a different set of strategies. I think at least initially, some of these strategies will be to use the people in these production operations in a more effective way. At least initially, we’re going to see some manual controls involved in profitability, with the safety of the operation, and with the environmental integrity. As we learn more and more, those manual controls are going to have to be replaced with automatic controls, from a purely practical point of view, because they’re going to become too fast for humans to deal with.
Here’s another indication of how things are changing: When you think about the chemical industry, the average tenure of a CEO in a chemical company is somewhere between 13 and 20 months. That’s a frightening concept. That means that these people have 13 to 20 months to prove themselves. So what do they do? Everything is designed for short-term gains, and it’s driving them nuts. It’s all going to catch up. Sooner or later, the group that’s looking beyond that and looking for the root cause is going to become more profitable, and those people that are playing the short-term gain game are going to be left by the side of the road.
I don’t believe there are many instances on the plant floor that can be brought under automatic control where we should go back to manual control. We should be trying to control as much as possible in an efficient, automatic way, while at the same time involving people more and more in the operation because of the business dynamic.
Edited by Peter Welander, firstname.lastname@example.org.
- The number of variables that have to be considered in a control strategy is growing in a way that includes more business-related elements.
- Control strategies that are adequate for running the process may not be capable of controlling new variables.
- Human controllers may need to fill the gap between needs and capabilities.