Process control systems, computer-based

A semiconductor microcircuit is a series of electrically intercoimected films that are laid down by chemical reactions. The successful growth and manipulation of these films depend heavily on proper design of the chemical reactors in which they are laid down, the choice of chemical reagents, separation and purification steps, and the design and operation of sophisticated control systems. Microelectronics based on microcircuits are commonly used in such consumer items as calculators, digital watches, personal computers, and microwave ovens and in information processing units that are used in communication, defense, space exploration, medicine, and education. 

Computer-based process control systems do not know how to plan, schedule, and implement process operations beyond the local confines of single processing units, as required by the evolving needs of computer-integrated manufacturing [9]. Planning of process operations requires the theoretical... 

Compute the valve flow coefficient The valve flow coefficient C is a function of the maximum steam flow rate through the valve and the pressure drop that occurs at this flow rate. When choosing a control valve for a process control system, the usual procedure is to assume a maximum flow rate for the valve based on a considered judgment of the overload the system may carry. Usual overloads do not exceed 25 percent of the maximum rated capacity of the system. Using this overload range as a guide, assume that the valve must handle a 20 percent overload, or 0.20(1500) = 300 lb/h (0.038 kg/s). Hence, the rated capacity of this valve should be 1500 + 300 = 1800 lb/h (0.23 kg/s). 

Up to the present time it has not been possible to demonstrate the ultimate reliability of characterizations based on random disturbances. However, the use of random disturbances offers great potential advantage in studying existing process control systems where upsets like step disturbances cannot be tolerated. Because of the extensive calculation required to reduce the random operating records to statistical-correlation functions, high speed digital computation is essential in this treatment. 

In the past, process control systems have been based on proprietary computer platforms, acting as "islands of information" from which production reports were printed out and stored as part of the critical production information. This situation is rapidly changing as most process control systems now operate on open standard platforms that are much easier to integrate. Recent development in control communication protocol standards has made such system integration even easier. Nevertheless, many process control systems currently used have been in operation for many years, leaving companies with the challenge of interfacing these proprietary systems in order to release the benefits of paperless operation. 

There would appear to be an appreciation amongst regulators that computer systems are extensively used throughout the drug manufacturing, packaging and distribution process. The computer systems covered by the inspections included MRP II, LIMS, spreadsheets, process control systems and network applications. Between these inspections, a large number of non-compliance observations were made and are summarized below. This summary is based on several hundred noncompliance observations made between the inspections. 

Sophisticated control systems have been developed in response to the high interdependence of several process variables coupled with the demands of very high output rates [15]. While many lines still utilize primarily manual controls, a growing number of blown film systems depend on computer-based measurement and control of all key process variables. These computer-based systems can make an important contribution to increasing efficiency, reducing costs, and increasing profits on high output lines. 

With so-called one-chip processors, modern semiconductor technology offers an inexpensive module which can perform all the functions of the central processor of a process computer. As a result, many new fields of application for computer-based solutions are being opened up, and the end of this development is not in sight. Hence the introduction of microprocessors into the control of cement manufacturing plant obviously suggests itself, and has indeed been successfully accomplished for certain special purposes. It should be borne in mind, however, that with the use of a process computer in a cement works rather less than 10% of the capital cost is spent on the central processor, as against more than 50% on software and engineering. The actual cost of a microprocessor is therefore only to a very limited extent determined merely by the hardware cost. Even so, the microprocessor is assured of a future in cement works, but more particularly as a powerful component unit of process control systems. 

In view of the increased emphasis placed on safe, efficient plant operation, it is only natural that the subject of process control has become increasingly important in recent years. Without computer-based process control systems it would be impossible to operate modern plants safely and profitably while satisfying product quality and environmental requirements. Thus, it is important for chemical engineers to have an understanding of both the theory and practice of process control. 

Distributed (or Digital) control system. A process control system based on computer intelligence and using a data-highway to distribute the different functions to specialized... 

It is often desirable to automate a process, peirticularly when a process is repeated for a number of cycles. This can be achieved with either microprocessor-based controllers or via computer programs to operate valves [26]. The process control system can also be used to monitor, record and change the separation conditions such as pressure, pH, conductivity, flow rate and temperature. Use of sensors allows feedback control of the process. These can be used to control flow rate and pressure and to detect the presence of air in the system. The emergence of protein from the column can be monitored by measuring the absorbance of the eluate and this can be used to initiate isolation of the product [26]. 

Monitoring and control of the production process will be performed by a combination of instrumentation and control equipment plus manual involvement. The level of sophistication of the systems can vary considerably. For example, monitoring well performance can be done in a simple fashion by sending a man to write down and report the tubing head pressures of producing wells on a daily basis, or at the other extreme by using computer assisted operations (CAO) which uses a remote computer-based system to control production on a well by well basis with no physical presence at the wellhead. 

They attend to and control different technical plants and systems, and they have to deal with all processes required. In data-based plants, controllers usually communicate with one or several local or central computers. 

The first set of case studies illustrates errors due to the inadequate design of the human-machine interface (HMI). The HMI is the boundary across which information is transmitted between the process and the plant worker. In the context of process control, the HMI may consist of analog displays such as chart records and dials, or modem video display unit (VDU) based control systems. Besides display elements, the HMI also includes controls such as buttons and switches, or devices such as trackballs in the case of computer controlled systems. The concept of the HMI can also be extended to include all means of conveying information to the worker, including the labeling of control equipment components and chemical containers. Further discussion regarding the HMI is provided in Chapter 2. This section contains examples of deficiencies in the display of process information, in various forms of labeling, and the use of inappropriate instrumentation scales. 

The case study described here concerns a human factors audit of a computer controlled process system which was being introduced in a distillation imit of a chemical plant. The unit was in transition from replacing its pneumatic panel instrumentation with the new system. However, control had not yet been transferred and the staff were still using the panel instrumentation. The role of the project was to evaluate a preliminary design of the computer-based display system and provide recommendations for future development. 

Traditional control systems are in general based on mathematical models that describe the control system using one or more differential equations that define the system response to its inputs. In many cases, the mathematical model of the control process may not exist or may be too expensive in terms of computer processing power and memory. In these cases a system based on empirical rules may be more effective. In many cases, fuzzy control can be used to improve existing controller systems by adding an extra layer of intelligence to the current control method. 

Radiofrequency spectroscopy (NMR) was introduced in 1946 [158,159]. The development of the NMR method over the last 30 years has been characterised by evolution in magnet design and cryotechnology, the introduction of computer-based operating systems and pulsed Fourier transform methods, which permit the performance of new types of experiment that control production, acquisition and processing of the experimental data. New pulse sequences, double-resonance techniques and gradient spectroscopy allow different experiments and have opened up the area of multidimensional NMR and NMRI. 

A detailed discussion of the application of digital computers and microprocessors in process control is beyond the scope of this volume. The use of computers and microprocessor based distributed control systems for the control of chemical process is covered by Kalani (1988). 

The main tools used to provide global projections of future climate are general circulation models (GCMs). These are mathematical models based on fundamental physical laws and thus constitute dynamical representations of the climate system. Computational constraints impose a limitation on the resolution that it is possible to realise with such models, and so some unresolved processes are parameterised within the models. This includes many key processes that control climate sensitivity such as clouds, vegetation and oceanic convection [19] of which scientific understanding is still incomplete. 

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