Design, analysis, and control of manufacturing processes through timely controlled measurements of essential quality and performance parameters are all part of process analytical technology. This helps ensure the quality of the end product (ICH Q8R2). This term has been around for a long time, yet it’s still relevant today because of how popular it is.
Analytical Process Control
Process control includes the methods used by industries, machines, and organisms to complete tasks. All complex systems, whether mechanical, electrical, or biological, whether man-made or natural, contains methods for process control. Continuous production industries including energy, oil refining, pulp and paper, and steel use process control extensively, as do complicated machinery like automobiles, planes, computers, and robots.
Automation and regulation of system activities or processes are two concepts that are closely related to computer science. Using high-quality, trustworthy standards to identify, describe, and manage processes is a difficulty in the business since processes grow so quickly. As a result, process control now encompasses not only the use of machines and computerized control mechanisms but also the coordination and accumulation of human expertise (“organizational memory”).
Process control is typically around-the-clock, “24/7” operation, with individuals in charge of it working in shifts. The energy industry is known for its strict adherence to process control standards. Crisis management, aviation and train control, armed forces, hospitals, police and rescue services, and communications all use it as normal practice. These industries are enormously valuable from an economic standpoint on a worldwide scale. Everyone is primarily concerned with preventing service outages while also making improvements to their existing operations. Process control must include information sharing between shifts, coordination of work processes, and the development of knowledge and learning among other things, according to all of the respondents. Although new or experimental tools may be difficult to use due to organizational culture challenges, the requirement for high quality and dependability as well as time- and safety-critical factors can obstruct their widespread use.
Process Control system
Knowing about IT architectures is essential if you want to grasp the many control mechanisms and processes that are available, as well as how they are embedded and how they interrelate. Many distinct information systems are used in process control. Different concepts are interpreted flexibly, therefore there are various ways to classify them. Vendors, users, products, and even continents all have different levels of adoption when it comes to usage. It’s easy to get lost in the semantics. The standard method of designing plant system architecture divides it into tiers of technical complexity.
Process control information systems are located in the lowest three layers, namely the field net, the process net, and the control net. The field network is in charge of overseeing the equipment used for both input and output. There are a number of components to the process net, such as PID (Proportional-Integral-Derivative) controllers and motor controls. It frequently includes advanced functions like sequences, batches, and optimization. Sectional or departmental control is implemented in the control net. Different departments within a company are in charge of different aspects of process control. Production management, automation/process control, maintenance, quality, laboratories, repair, service, spare parts, raw materials, stock, and materials are typical areas of process control responsibility.
Process Control Network Interconnectivity
It is the responsibility of each department, which has its own information demands and processing procedures, but they are also interrelated. Each department is accountable for a variety of actions. Different systems often speed up interconnection. Among these are systems for general use as well as process information management and automation systems, as well as logic systems and systems for a particular use (e.g., machine condition monitoring and diagnosis systems). Process monitoring, predetermined tasks, disruption control, information exchange, knowledge management, ongoing development, and learning are all responsibilities of these systems.
Information needs must be met at the field, process, control, plant, and corporate levels through hardware and information systems. These systems must also be interconnected in a way that is simple for the end-user to utilize. Maintaining system designs and preventing them from becoming overly complex for end-users is a challenge for IT staff.
On the control-net layer, the work of the operational crew people can be seen. They monitor processes on a regular basis and carry out predetermined activities, such as beginning batches or completing sequences. When a problem arises, the focus of the operator shifts to getting things back to normal as quickly as feasible. Most of the time, a big amount of information is handled quickly. This can result in long-term disruptions requiring an extensive exchange of skills and information. Most staff members have learned something when a solution is identified. Ideally, they share what they’ve learned with other colleagues. The method is always evolving as a result of gathered knowledge. This “organizational memory” field is still in its infancy as far as higher levels of process control are concerned.
Process Control and Organizational Memory
There has been a sea change in automation. New methods are revolutionizing process management, as opposed to older ones, which mostly followed the advancements in the process. In today’s world of automation, open information system architecture has become critical. These advanced control approaches are integrated with knowledge management tools such as memoranda and reports. Increasing production line efficiency necessitates a new dimension known as the “information network.” Those in charge of disruption control or production optimization can use this data, along with historical and real-time process data, to make better decisions.
Using a process control system with standardized user interfaces and tools for collecting and storing process data, the problem is to select, save, and disseminate the correct information to the right person at the right time. Other systems can access the collected data using normal database interfaces as part of the broader architecture, as well.