02 April 2018
As new technology influenced factories and plants, new approaches have appeared to maximise benefits. One such idea is ‘profitable efficiency’, which is profitability control cascaded to process control to maximise operational profitability in real time. While this is a new execution method, its concept is already deeply ingrained within 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 significantly beyond single-loop feedback control. For example, multi-loop cascade control, feedforward control, and coordinated multiple variable control utilise dynamic process models to enable sophisticated control strategies. Fundamentally, real-time control involved making and acting on decisions within the period defined by the time constant of the process being controlled. In other words, the timing is defined by the process being controlled, rather than human time schedules. 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 can be categorised into four basic types. There? are manual and automatic control strategies, as well as feedback and predictive strategies, which can utilise 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 that information and to realise a positive result, we say they are ‘empowered’. So, an empowered workforce relies on operators being given the tools necessary to effectively serve as controllers. It was understood that any improvements in efficiency could be translated directly into improvements in operational profitability. But this is no longer the case.? Since the early 2000s, the speed of industrial business has steadily increased, triggered by the deregulation of electric 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 that even though plants might actually increase their energy consumption, their energy bill could increase. The frequent fluctuations in electricity prices caused a domino effect across other energy sources and raw materials. To deal with the unstable costs, industrial companies started changing the price of their products more frequently. This effect is most easily 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 must also determine the best time to produce, which can sometimes diminish the importance of operational efficiency – 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 IT departments and enterprise resource planning (ERP) suppliers for solutions. Few, if any, realised the desired results, primarily because the IT teams and ERP software were both experienced in solving traditional management problems, but not real-time control problems. The correct 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?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 by 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. As engineers gain more insight into the factors that drive the decisions made by operators, automated control will eventually be developed. The next challenge was determining the relationship between traditional process control and real-time profitability control. Clearly, 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, 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 realise 100% ROI in a very short time – often under six months – with sustainable results that last and improve for years. 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. Additionally, embedding the RTA models throughout the operation enables you to measure operational profitability for any initiative that impacts the performance of the operations. With these measures, managers can learn on how to shift the focus of their resources on 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. It has proven to drive strong results because it allows you to keep both your process and profits in control. Peter Martin is vice president, Innovation and Marketing Process Automation at Schneider Electric.
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