Process Control

Process control encompasses the means by which tasks are accomplished by industries, machines, or organisms. Process control mechanisms are found in all complex systems, whether they are mechanical, electrical, or biological—human-made or natural. Major applications of process control are found in such continuous production industries as energy, oil refining, pulp and paper, and steel, and in such complex machines as cars, planes, computers, and robots.

In the context of computer science, process control is defined as the use of a computer system to automate and regulate the operations or processes of a system. One of the challenges in the industry regards the fact that processes often proliferate faster than they can be identified, defined, and managed using high-quality, reliable standards. Because of this, process control has increasingly come to include the coordination and accumulation of human expertise ("organizational memory") as well as the use of machines and computerized control mechanisms.

Process control is generally a continuous, "24/7" working effort; people responsible for process control are organized into round-the-clock staff shifts. Continuous process control is typical of the energy industries. It is also standard in crisis management, air and train control, military forces, hospitals, police and rescue services, and communications. The global economic value of these sectors is huge. All are centrally interested in avoiding operational interruptions while simultaneously improving their processes. All express the need to include, as part of process control, the sharing of information between shifts, the coordination of work processes, and the development of expertise and learning. Business culture issues, the need for high standards of quality and reliability, and time- and safety-critical concerns can prevent easy adoption of new or experimental tools, however.

Process Control Structures

An understanding of information technology (IT) architectures is necessary to comprehend the available variety of control mechanisms and processes, the ways in which they are embedded, and how they need to interrelate. Process control consists of numbers of different information systems. There are multiple ways to categorize them because different concepts are interpreted flexibly. Usage varies according to vendor, user, product, or even continent. The semantics can be confusing. Most traditional ways of defining plant system architecture divide it into technical layers, as in Figure 1.

Figure 1 is an illustration of a generic system architecture. Information systems for immediate process control are contained in the bottom three layers, which are the field net, the process net, and the control net. The field net manages input and output equipment. The process net defines PID (Proportional-Integral-Derivative) controllers, motor controls, interlocking and basic logic, and calculations. It usually contains advanced features such as sequences, batches, and optimizing. The control net is where section- or department-wide control is implemented. The various functions of process control are the responsibility of different departments of an organization. Areas of process-control responsibility can usually be divided into production management, automation/process control, maintenance, quality, laboratory, repair, service, spare parts, raw material, stock, and materials.

Interconnectivity of Process Control

Each department is responsible for a variety of actions, each of which has its own information needs and handling mechanisms, but these are also interconnected. Interconnection is usually expedited by different systems. These include general purpose systems, process information systems, automation systems, logic systems, and special purpose systems (e.g., machine condition monitoring and diagnosis systems). These systems are responsible for a variety of activities including process monitoring, predefined tasks, disturbance control, information exchange, knowledge management, continuous development, and learning. Hardware and information systems have to span information needs at the field, process, control, plant, and corporate levels. Furthermore, these systems need to be interconnected in a user-friendly way. A challenge for IT personnel is to maintain system architectures and prevent them from becoming too complex for end-users.

The work of operating crew personnel can be illustrated on the control-net layer. They routinely monitor processes and perform predefined tasks such as starting batches or accomplishing sequences. When a disturbance occurs, operators concentrate on recovering a normal state as soon as possible. A large amount of information is handled, usually, in a short time. Sometimes process interruptions may last for weeks, and much expertise and information exchange is needed. When a solution is found, staff members have usually learned something; ideally, they share this experience with others. Based on accumulated expertise, the process continuously evolves. The development of higher levels of process control in this field of "organizational memory" is still in its infancy.

Organizational Memory and Process Control

The nature of automation has changed radically. Whereas earlier systems mainly followed process developments, new methods are now revolutionizing process management. Open information systems architecture has become an essential part of automation. Advanced control methods, such as fuzzy logic and neural networks, are combined with information and knowledge tools, memos, and reports. The so-called "knowledge network" is a new dimension that plays a vital role in increasing production line efficiency. When combined with history and real-time process data, it is a powerful decision-making asset for those responsible for handling disturbance management or production optimization.

The challenge is to be able to select, save, and distribute the right information to the right person at the right time with a process control system that uses standardized user interfaces and tools for collecting and storing process data. It also makes the collected data available to other systems through standard database interfaces within an overall architecture.

Mike Robinson and Mikko Kovalainen

Bibliography

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