Achieving profitable efficiency through process control
Profitability control cascades to process control to maximize operational profitability in real time. While this is a new execution method, its concept is already ingrained in the DNA of process control.
The primary objective of process and logic control is to improve the efficiency of an operation. This has traditionally been measured by determining whether or not throughput has increased while energy and material consumption have decreased.
To improve efficiency, a feedback control loop measures the variables that need to be controlled, determines the variation from the desired set point, and adjusts the variables to move toward the set point.
Since the 1960s, process control has advanced beyond single-loop feedback control. Multi-loop cascade control, feed forward control, and coordinated multiple variable control use dynamic process models to enable sophisticated control strategies.
Real-time control involves making and acting on decisions in a period of time defined by the process being controlled. Decisions being made on human schedules are referred to as management decisions, while decisions made on process schedules are referred to as control decisions.
Traditional control strategies include four basic types: manual and automatic control strategies, and feedback and predictive strategies, which can use automatic or human control. When humans are provided the information they need to make effective real-time control decisions, as well as the tools they require to act on this information and to realize a positive result, they are empowered. An empowered workforce relies on operators being given the tools necessary to effectively serve as controllers.
It was once understood that improvements in efficiency could be translated into improvements in operational profitability. This is no longer the case. Since the early 2000s, the speed of industrial business has increased steadily, triggered by the deregulation of electrical power. As electrical power was deregulated, the supply-to-demand ratio on the grids started to fluctuate. Energy suppliers and grid managers tried to deal with these fluctuations by increasing the price of energy when the demand was high and supply was low and reducing the price of energy when the demand was low and supply was high.The result was while plants might increase their energy consumption, their energy bill could increase in the process.
The frequent fluctuations in electricity prices caused a domino effect across other energy sources and raw materials. To deal with unstable costs, industrial companies started changing the price of their products more frequently. This effect is seen in energy markets, but it also affects consumer production. Today, in an increasingly speedy industrial market, not only must plant managers decide how much to produce, but the operators also must determine the best time to produce, which can sometimes diminish the importance of operational efficiency. That is, it might be more profitable to run the plant less efficiently, according to the traditional efficiency measures, to more cost-effectively meet market demand and opportunity.
Process control for improved operational efficiency no longer had a direct impact on improved operational profitability and new approaches were required to deal with the ever-increasing real-time dynamics of industrial business variables.
The first response was to turn to information technology (IT) departments and enterprise resource planning (ERP) suppliers for solutions. Few, if any, realized the desired results, primarily because the IT teams and ERP software were both experienced in solving traditional management problems, not real-time control problems. The solution involved understanding that, as operational profitability fluctuated more rapidly, management decisions had become control decisions. In other words, the solution had to be approached from the perspective of real-time control.
Real-time control is predicated on the availability of real-time measurements. The first problem to be addressed was measuring operational profitability in real time. Engineers developed a number of engineering-based approaches to solve this problem. New key performance indicators (KPIs) with monetary context were calculated, but they had little credibility with the cost accounting teams who actually measure the performance of the operations because they used different metrics.
The correct approach was found to involve calculating the accounting factors of the operation in real time. This can be done using a combination of sensor-based data from the process and financial data to calculate the cost and profit points across industrial processes. This is referred to as real-time accounting (RTA).
Once these RTA factors became available, they could be used to control operational profitability very dynamically. Providing real-time feedback to operators allows them to determine the financial impact of their actions and empowers them to learn how to operate the process most profitably. The result is manual, real-time profit control. Automated control will be developed as engineers gain more insight into the factors that drive the decisions made by operators.
The next challenge was determining the relationship between traditional process control and real-time profitability control. Operational profitability cannot be manipulated if the efficiency of a plant is not well controlled. There is a very classic control relationship between profitability control and efficiency control. It involves a cascade control strategy with profitability control as the primary loop, with cascading set points to the process control serving as the secondary loops.
Implementing profit control strategies over process control strategies results in a new class of real-time control strategies, referred to as profitable efficiency. Implementing profitable efficiency throughout an industrial operation tends to drive new and improved levels of operational profitability that realize 100% return on investment (ROI) in a very short time. Additionally, making the real-time accounting measures the primary performance indicators of industrial operations ensures their sustainability and often enables continual operational profitability improvements for the life of the plant.
Embedding RTA models throughout the operation enables the measurement of operational profitability for any initiative that impacts the performance of the operations. With these measures, managers can learn how to shift the focus of their resources to activities that add more value.
The field of real-time control is expanding from traditional process and logic control for operational efficiency improvements to other real-time domains, such as operational profitability. As new control strategies are applied to new domains, the performance of industrial operations will improve significantly, to levels never before expected. Profitable efficiency, by ceding profitability control to process control, represents one new approach and allows the user to keep both the process and profits in control.
Peter Martin is vice president, Innovation and Marketing Process Automation at Schneider Electric. This article originally appeared April 2, on the Control Engineering Europe website. Edited by Chris Vavra, production editor, Control Engineering, CFE Media, email@example.com.
Keywords: efficiency, process control
Profitable efficiency is a relatively new concept, but it is already quite common in process control applications.
Implementing profitable efficiency throughout an industrial operation tends to drive new and improved levels of operational profitability.
Profitable efficiency allows the user to keep both the process and profits in control.
What other benefits could profitable efficiency provide manufacturers?