Find the right strategy for control automation
The term control automation strategy has no "official" definition. It was chosen to demonstrate that the traditional roles of automation in manufacturing have changed over the years and the lines that separate them is becoming increasingly blurred. The types of control systems used in manufacturing plants depend on the processes and operations companies use to produce their products.
The term control automation strategy has no "official" definition. It was chosen to demonstrate that the traditional roles of automation in manufacturing have changed over the years and the lines that separate them is becoming increasingly blurred.
The types of control systems used in manufacturing plants depend on the processes and operations companies use to produce their products. Some of these categorizations are obvious. For example, look in any refinery process and you will probably find some type of distributed control system (DCS) (Fig. 1). On the other hand, go to a plant that manufactures discrete electronic or mechanical assemblies and you will probably find programmable logic controllers (PLCs).
What about batch-oriented industries such as pharmaceuticals or food and beverage? There you will find a blend of process and discrete manufacturing. It has been said that the difference between process and discrete industries is that process industries make stuff and discrete industries make things. Even though process and discrete traditionally represent opposites, they form a continuum (Fig. 2).
The differences, similarities, and the number of product types your plant manufactures influence control schemes as well. The complexity of automation differs according to manufacturing methods, regulatory issues, documentation and reporting requirements, and maintenance strategies.
Plants using automation to control their manufacturing processes gain a competitive advantage. Automation enables companies to manufacture more products quicker, and with less scrap, rejects, or defective materials. However, they must use the right automation for the right process, which is not always easy to determine.
For the sake of categorization, this article refers to several control automation strategies with varying degrees of overlap. These control automation categories include discrete, distributed, and hybrid control.
When someone mentions the term discrete control, it is generally understood to mean controlling by means of a PLC. The PLC has been around since the mid 1960s. Plants have become comfortable with them to the point of taking them for granted at times.
Perhaps it is an oversimplification to assume that discrete control equals discrete industry or vice versa. PLCs were invented to take the place of electromechanical relays, which were the workhorses of machine control for decades. Now we can say that PLCs were workhorses for decades too. But they have not been replaced. However they have been hot-rodded, emulated, and even redefined.
ARC Advisory Group coined the term programmable automation controller to emphasize the advancements in performance that PLCs offer (Fig. 3). When companies began to configure and program PLCs to make them operate as PCs or distributed controls, as well as integrating motion control, it was time to shift the paradigm and create a new buzzword.
More than just another three-letter acronym, this shift increased the migration toward blurring the lines between discrete and process, as well as PLC and DCS functionality.
Operators that toured the plant with clipboards operated early continuous processes manually. They took readings from indicators and gauges and used these values in calculations that determine how the process was behaving. If they were lucky, their ciphering was accomplished just in time for the next round of readings and valve adjustments.
Pneumatic control appeared on the scene. Eventually this technology migrated to a centralized control room. Centralizing the control function brought the process to the operator. It also increased the complexity of process control systems. The advantage was that operators were able to minimize the walk-around time, thereby allowing more time for calculations.
Electronic controls became rugged enough to withstand an industrial environment soon after World War II. New sensors began to appear, allowing some measurements to be taken inline, instead of operators having to gather laboratory samples. The relative miniaturization enabled more control functions to reside in the centralized control room, making it even more complex. However, it necessitated more wiring from the control room to the field sensors. This presented information management problems to the operators and signal management challenges to the plant and/or instrument engineers.
As the price of mainframe computers came down, they began to show up in centralized control rooms. Advancements in hardware and programming languages enabled computers to deal with these control data. However, mainframe computers were designed for business. Costs of "automated" control were climbing. Wiring became even more complex. Engineering expertise for system design and labor required for installation of lines and making terminations were major challenges.
A serious control problem emerged from this scenario. If the computer failed, it could shut down the entire plant. To get around this, backup controllers were used. This meant that plants had to buy two sets of controls for everything, just to have the necessary reliability of a duplicate control system. Because of this redundancy, sometimes the computer did the controlling; and frequently, analog instruments kept the plant operating. This required operators to know how to operate computers as well as be proficient in process control. These operators were scarce and expensive.
The influence of computers brought about a leap in the evolution of DCS. The use of digital technology in control systems changed the way automated process control was accomplished.
The emergence of data communication networks paved the way for control intelligence to migrate from the control room to the actual process itself. Proprietary networks, many of which have evolved into "open" fieldbuses (or as open as they can be at this point in time), made it possible to locate controls closer to the point of sensing and valve operation, instead of the centralized control room. Enter, distributed control.
Gartner, Inc. defines distributed control as, "A form of direct digital control for process automation, distributing specialty-purpose controllers across a common communication network throughout a manufacturing plant. In a DCS, measurement, control, and communications are distributed in function and location. By partitioning and distributing control functions, local controllers throughout the plant remain in control of the process if central control room consoles are lost. Likewise, if one local control station fails, other local controllers continue to operate. DCSs are usually deployed in fault-tolerant modes using redundant system configurations to achieve high measures of system availability."
A typical DCS consists of subsystems that are functionally integrated but may be physically separated and remotely located. They generally share at least one function within the system. This may be the controller, the communication link, and/or the display device.
Although the control is near many individual plant processes, it doesn't mean the data must stay there. Because of the PC, fieldbuses, industrial Ethernet, and other automation and communication technologies, control can remain at the process while the data are distributed throughout the enterprise — whether across the plant or across the world.
Control automation architecture trends indicate that more intelligence is appearing on the plant floor, while more information is distributed throughout the enterprise. The traditional operator interface is migrating to local control areas where more processing power and capacity exist, and to the enterprise level to provide better business information.
Controller functions are migrating to plant floors within smart field devices. Smart sensors diagnose themselves, and the centrally located SCADA diagnoses the system. Proprietary networks will no longer be necessary for speed and capacity. Standards are emerging to make this transformation possible. However, these advancements still won't solve every problem.
The three factors that influence today's DCS market are replacement of old equipment, increasing scalability requirements, and the need for more comprehensive systems. Process plants have a very large installed base of DCS equipment, although the age of some of them are approaching 20 years. Companies are looking for cost-effective ways to upgrade their systems because they can't justify the capital expense of ripping out the old and putting in the new.
DCS vendors introduced smaller systems to take back some of the business that was claimed by PLCs and industrial PCs a decade ago. The promise was that these smaller, less expensive "starter" DCS offerings could be upgraded to larger systems. This "grow as you go" scalability kept DCS relatively competitive.
Legacy DCS excelled at regulatory control. But advanced control functionality had to be delegated to a minicomputer. But modern DCS applications have these advance functions built in — along with enterprise functions such as asset management, manufacturing execution system, and production management.
DCS vs. PLC
The longstanding debate of which control scheme was better for which process has largely been a contest between PLCs and DCS offerings. This argument continues for many plants that are not wholly continuous process or discrete manufacturers. As PLCs offer more PC and DCS-type functionality and DCSs offer more discrete logic type functionality, they will continue to vie for bigger slices of the control automation pie.
Some plants installed PLCs under the DCS architecture to do motor and discrete control; pass stop/start and status back to the DCS for the process interlocks; and for the HMI display. A DCS can emulate the discrete functions of a PLC, usually at a higher cost; and a PLC can emulate the continuous control of a DCS. However, what separates the DCS from the PLC, and makes it more expensive, is:
The ability to modify the configuration and programming of both the controllers and the HMI on-the-fly without having to take the system off line to recompile or reboot the system
The ability to add or remove I/O cards from a controller without taking the process off-control
The availability of redundancy throughout the process (including I/O) that is transparent to the operator
The ability to remove and replace any single piece of hardware without taking the process off-control.
Advances in memory media
Microprocessor speeds and costs
Requirements for complex functionality such as process model control, neural networks, fuzzy logic, and other advanced control technologies.
The importance of asset optimization in the DCS value proposition
Emphasis on return in assets
Control system migration strategies
Criticality of initial costs in relation to life cycle costs
The importance of real-time performance monitoring.
According to ARC, hybrid industries will continue to have the highest rate in growth.
Whether your process is continuous, batch, discrete, or a combination thereof, it is to your best interest to know your process and apply the control automation strategy that makes the most technological sense and offers the most benefits to your business.
PLANT ENGINEERING magazine extends its appreciation to ABB; ARC Advisory Group; AutomationDirect; Emerson Process Management; Honeywell; Invensys Process Systems; Phoenix Contact; Rockwell Automation; Schneider Electric; Siemens Energy & Automation; and WAGO for their assistance in the preparation of this article. For more information about these and other control automation strategies, go to www.plantengineering.com .
A recent study by ARC Advisory Group identifies some of the factors that will influence choices and growth in the control automation markets:
But how much of the control function do you put at the work site level? There is a point of diminishing returns where it is not cost-effective to put the memory and intelligence at the sensor level. For example, limit-switch counts can be fed to the asset management system to generate a work order to lube the limit switch arm. However, there is a thick gray line somewhere in the control automation scheme. Vision sensing is more complex than a limit switch or a proximity sensor.
Control automation seems to follow the 80/20 rule — 80% is information, data handling, data marshalling, and time stamping, and 20% is pure hard logic. This ratio is growing. It will be 90/10 soon because so many eyes are on the data. Companies are asking, "How much more business can we squeeze out of the data?"
The products your plant manufactures determine automation and control strategies. A food and beverage manufacturer may have very different automation requirements from a manufacturer of machinery, which will have different requirements from a contract-electronics manufacturer. However, there may be more similarities among automation designs than there are differences. That certainly was not the case a decade ago.
Most processes include a combination of continuous control needs, such as flows and temperatures; and discrete control requirements, such as on/off circuits. A traditional process approach to meeting these differing needs has been to work solely within a DCS environment, where the continuous control requirements are easily satisfied, but configuring discrete control can be difficult.
The other option has been to buy a DCS for continuous control and a PLC for discrete control, which doubles your configuration, integration, installation, and maintenance efforts.
A hybrid system unifies the best features of DCS and PLC technology in a highly integrated, yet open environment. With systems for batch and plant-wide automation, critical control applications, and area control applications, these systems can be implemented stand-alone or as seamlessly integrated components of a comprehensive, multi-plant strategy (Fig. 4).
Function blocks can be used for continuous control. Discrete control is defined via ladder logic. Sequential function charts support complex sequencing. Structured text offers a text-based alternative for applications such as optimization and complex calculations.
There are a growing number of industries that fall into this hybrid category. It is for this reason that the hybrid control automation systems market has become such a competitive landscape.
Advancements in fieldbuses, smart sensors and actuators, and the intelligence of diagnostics, open a whole new world to communication beyond start/stop, open/close, and flow/no flow. DCS and discrete control strategies are still entrenched in their traditional industries. However, tremendous growth in the hybrid middle ground presents growth opportunities for the hybrid control system market — along with fierce competition.
Factors that will affect the control automation landscape include:
- Events & Awards
- Magazine Archives
- Oil & Gas Engineering
- Salary Survey
- Digital Reports
Annual Salary Survey
Before the calendar turned, 2016 already had the makings of a pivotal year for manufacturing, and for the world.
There were the big events for the year, including the United States as Partner Country at Hannover Messe in April and the 2016 International Manufacturing Technology Show in Chicago in September. There's also the matter of the U.S. presidential elections in November, which promise to shape policy in manufacturing for years to come.
But the year started with global economic turmoil, as a slowdown in Chinese manufacturing triggered a worldwide stock hiccup that sent values plummeting. The continued plunge in world oil prices has resulted in a slowdown in exploration and, by extension, the manufacture of exploration equipment.
Read more: 2015 Salary Survey