Processes control

Control in one form or another is an essential part of any chemical engineering operation. In all processes, there arises the necessity of keeping flows, pressures, temperatures, compositions, etc. within certain limits for reasons of safety or specification. It is self-evident that automatic control is highly desirable, as manual operation would necessitate continuous monitoring of the controlled variable by a human operator and the efficiency of observation of the operator would inevitably fall off with time. Furthermore, fluctuations in the controlled variable may be too rapid and frequent for manual adjustment to suffice. 

In its simplest form, the control of a process is most often accomplished by measuring the variable it is required to control (the controlled variable), comparing this measurement with the value at which it is desired to maintain the controlled variable (the desired value or set point), and adjusting (in a prescribed way until the desired value is attained) some further variable (the manipulated variable) which has a direct effect on the controlled variable. 

Control of the process can be carried out very accurately if the freezing and the drying behaviour of a product is known. During freezing, the temperature of the product is measured and the cooling rate carefully controlled until the required final temperature has been reached. 

Control of the product temperature using temperature sensors is possible only during freezing and at the beginning of primary drying since it is only during these process steps that sensors are completely immersed in the product. Since the ice around a sensor usually sublimates more quickly than in the other areas, the temperature thus measured cannot be used for a reliable control of the process. 

An important precondition for applying the BTM-method is a very vacuum-tight design of the chamber. This is the only way to ensure that the rise in pressure caused by a possible leak in the chamber remains negligible compared to the rise in pressure caused by the accumulating water vapour. For this reason, the integral leak rate of the drying chamber must be 10 mbarls .  

Process control is the essence of modem factory systems. It is imperative at all times to have the process fully under control and for full records to be kept. 

Note For high-throughput items, display trays can be used. 

Adequate process control and its associated instrumentation are essential for product quality control. The goal in some cases is precise adherence to a control point. In other cases, maintaining the temperature within a comparatively small range is all that is necessary. For effortless controller tuning and the lowest initial cost, the processor should select the simplest controller (of temperature, time, pressure, melt-flow, rate, etc.) that will produce the desired results. 

In order for a process to be controllable by machine, it must represented by a mathematical model. Ideally, each element of a dynamic process, for example, a reflux drum or an individual tray of a fractionator, is represented by differential equations based on material and energy balances, transfer rates, stage efficiencies, phase equilibrium relations, etc., as well as the parameters of sensing devices, control valves, and control Instruments. The process as a whole then is equivalent to a system of ordinary and partial differential equations involving certain independent and dependent variables. When the values of the Independent variables are specified or measured, corresponding values of the others are found by computation, and the information is transmitted to the control Instruments. For example, if the temperature, composition, and flow rate of the feed to a fractionator are perturbed, the computer will determine the other flows and the heat balance required to maintain constant overhead purity. Economic factors also can be incorporated in process models then the computer can be made to optimize the operation continually. 

For control purposes, somewhat simplified mathematical models usually are adequate. In distillation, for instance, the Underwood-Fenske-Gilliland model with constant relative volatilities and a simplified enthalpy balance may be preferred to a full-fledged tray-by-tray calculation every time there is a perturbation. In control situations, the demand for speed of response may not be realizable with an overly elaborate mathematical system. Moreover, in practice not all disturbances are measurable, and the process characteristics are not known exactly. Accordingly feedforward control is supplemented in most instances with feedback. In a well-designed system (Shinskey, 1984, p. 186) typically 90% 

The development of a mathematical model, even a simplified one that is feasible for control purposes, takes a major effort and is well beyond the scope of the brief treatment of process control that can be attempted here. 

What will be given is examples of control loops for the common kinds of equipment and operations. Primarily these are feedback arrangements, but, as mentioned earlier, feedback devices usually are necessary supplements in primarily feedforward situations. 

A control mechanism is introduced that makes changes to the process in order to cancel out the negative impact of disturbances. In order to achieve this, instruments must be installed to measure the operational performance of the plant. These measured variables could include 

While this takes some account of operation under different conditions, it does not account for the dynamic transition from one state to another. Are these transitory states likely to have a significant influence on the optimality  

Batch processes are, by their nature, always in a transitory state. This requires the dynamics of the process to be optimized, and will be considered in Chapter 14. However, the control systems required to put this into practice will not be considered. 

9 THE NATURE OF CHEMICAL PROCESS DESIGN AND INTEGRATION - SUMMARY 

Chemical products can be divided into three broad classes commodity, fine and specialty chemicals. Commodity chemicals are manufactured in large volumes with low added value. Fine and specialty chemicals tend to be manufactured in low volumes with high added value. The priorities in the design of processes for the manufacture of the three classes of chemical products will differ. 

Automatic control is an essential feature of large-scale continuous processes. Many modern chemical plants are so complex that it would be impractical, unsafe and unprofitable to run them manually. 

By its nature process control is concerned with the dynamic behaviour of systems. It is no longer sufficient to make the steady-state assumption. Material and energy balances for unsteady systems must include the accumulation terms so far omitted. Because of the extra mathematical complexity involved in a quantitatve treatment of control this section will, instead, concentrate on general concepts rather than detailed analysis of 

The use of instruments that log and archive data facilitates remote monitoring of process performance and can improve plant troubleshooting and optimization and provide high-level data for enterprise-wide supply chain management. 

The electronic equipment and systems technology available for process control continues to evolve rapidly. Because of the pace of innovation, industry-wide standards have not been able to keep up consequently different manufacturers systems usually use proprietary technology and are often not fully compatible with each other. The implementation of the ISA SP50 Fieldbus standard is expected to substantially 

A detailed treatment of digital technology for process control is beyond the scope of this volume. Kalani (1988), Edgar et al. (1997), and Liptak (2003) all provide excellent reviews of the subject. Mitchell and Law (2003) give a good overview of digital bus technologies. 

Bertrand, L. and Jones, J. B. (1961) Chem Eng, NY 68 (February 20) 139. Controlling distillation columns. 

Buckley, P. S., Luyben, W L., and Shunta, J. P. (1985) Design of Distillation Column 

Reprinted with permission from N. Nakajima, W. J. Shieh and Z. G. Wang, International Polymer Processing, 1991, 6, 4, 290. Copyright 1991, Hanser Publishers. 

This discussion will be limited to the control of the internal mixer only. Uses of the roll-mill also require control, but in this case, the material is visible to the operator who makes the appropriate adjustments. 

Other indicators to monitor are the torque-time curve and the movement of the ram. Also, pressure tapping may be explored. Before discussing these, it is worthwhile to examine some of the causes of time-wise reproducibility problem. Even if the charging of the material is done in the same way each time, the mutual positions of two rotors with respect to wings are not the same. If there is a difference in the rotational speed of the rotors, they meet at the same mutual position after so many revolutions. The question is whether or not the charging may be automated in such a way for the rotors to accept the material at the same mutual position every time. 

important is the ease of material movement around the mixing chamber. Stagnation and impinging motions may contribute to the reproducibility problem. This has already been discussed (see section 11.10.3) in conjunction with efficiency of mixing [15]. 

The amplitude of oscillation in torque-time curve or that of the ram movement decreases as the contents becomes more homogeneous. In order to use these or total energy for deciding the endpoint, the dispersion must be examined ahead of time to assure a satisfactory result. The reproducibility in the same type mixer but different machines may be a problem. There may be a difference in the extent of wear of the rotor blades. The cooling surface may have scale build-up such that the cooling efficiency may be different. 

All processes involved in design, manufacture, use or servicing activities should be subject to documented control procedures. These process controls shonld be developed where the absence of such procedures would have an adverse effect on 

An example of a quahty plan for the control of transport operations can be found in Safety Series No. 113 [1V.3]. 

Processes affecting the finished product/service quality, where the required quality cannot be verified by post-process examination alone, and where pre-qualification of the process is necessary, e.g. welding or heat treatment, should be controlled in accordance with documented procedures. Such procedures should refer to relevant codes, standards, specifications or dedicated requirements. Where specified, measures should be taken to ensure that these processes are accomplished by qualified personnel, procedures and equipment. 

Documented procedures should provide for in-process, final, and in-service inspection carried out during all phases of testing, production, transport and maintenance against specified requirements. These procedures should include provision for measuring and test equipment used to be calibrated, adjusted and maintained at defined intervals. 

Receipt inspection, in-process inspection, and final inspection measures should be planned and carried out to meet the requirements specified in regulations, standards, design and manufacturing documents, transport, servicing, maintenance, and operating procedures, instructions, applicable quality plans, etc. Essential criteria to be included in such inspection measures can be found in Safety Series No. 113 [IV.3]. 

In order to operate a process facility in a safe and efficient manner, it is essential to be able to control the process at a desired state or sequence of states. This goal is usually achieved by implementing control strategies on a broad array of hardware and software. The state of a process is characterized by specific values for a relevant set of variables, eg, temperatures, flows, pressures, compositions, etc. Both external and internal conditions, classified as uncontrollable or controllable, affect the state. Controllable conditions may be further classified as controlled, manipulated, or not controlled. Excellent overviews of the basic concepts of process control are available (1 6). 

Process Systems. Because of the large number of variables required to characterize the state, a process is often conceptually broken down into a number of subsystems which may or may not be based on the physical boundaries of equipment. Generally, the definition of a system requires both definition of the system s boundaries, ie, what is part of the system and what is part of the system s surroundings and knowledge of the interactions between the system and its environment, including other systems and subsystems. The system s state is governed by a set of appHcable laws supplemented by empirical relationships. These laws and relationships characterize how the system s state is affected by external and internal conditions. Because conditions vary with time, the control of a process system involves the consideration of the system s transient behavior. 

Process systems are broadly categorized as self-regulatory and nonself-regulatory. The former is one in which a change in an external condition can cause the system to move from an initial steady state to another steady state without additional external intervention. The latter, a nonself-regulatory process system, does not achieve another steady state without additional control action once the first external change occurs. 

Generic Control Strategies. The two generic strategies for process control are feedback and feedforward control. Most process control strategies are based on one or a combination of these strategies (1 3). 

Some of the inherent advantages of the feedback control strategy are as follows regardless of the source or nature of the disturbance, the manipulated variable(s) adjusts to correct for the deviation from the setpoint when the deviation is detected the proper values of the manipulated variables are continually sought to balance the system by a trial-and-error approach no mathematical model of the process is required and the most often used feedback control algorithm (some form of proportional—integral—derivative control) is both robust and versatile. 

The development of powerful computer controls and programs has greatly accelerated integrating process variables with a goal of zero defects at the 

METHOD WEAR EXPENSE SPEED DEGREE WASTE PROBLEM HAZARD CAUSED 

Hand cleaning Dry-blast with sand or other 2 5 5 10 5 No No e 

MOLD AND CLAMP Clamp Tonnage Mold Temperature Cavity Pressure 

Botch To Batch Viscosity Index Changes Batch To Batch Density Changes Addition Of Color Concentrates Moisture 

Under the working assumption that the catholyte is perfectly uniform, changes in the feed concentration perse have no effect on the process. The dilution value of the recycle stream in Fig. 6.9 is then proportional to the difference between its concentration and that of the catholyte. On a weight basis, the required flow rate is inversely proportional to the same quantity. 

When the catholyte concentration is changed at a constant feed concentration, the situation is different. The mass and energy balance in the catholyte chamber will change. As the catholyte concentration goes down, more dilution is required in order to reach the lower concentration. At the same time, the amount of water evaporated into the hydrogen 

Stream increases because of the higher vapor pressure. This must be replaced by adding more recycle. The calculated recycle flow therefore is more sensitive in this mode. 

The actual changes here are about 18% greater than those estimated. 

The example assumed a constant water transport coefficient (WTC). This is not a realistic assumption, because the coefficient depends, among other things, on the NaOH concentration. The extent of this dependence is a function of other variables and on the type of membrane used. A single relationship between WTC and operating variables cannot be assumed. 

On typical grass-roots, chemical processing facilities, as much as 10% of the total capital investment is allocated to process control equipment, design, implementation, and commissioning. Process control is a very broad topic with many distinct aspects. The following possible sub-topics give some idea of the full breadth of this topic  

In the field, the topic of process control includes the selection and installation of sensors, transmitters, transducers, actuators, valve positioners, valves, variable-speed drives, switches and relays, as well as their air supply, wiring, power, grounding, calibration, signal conditioning, bus architecture, communications protocol, area classification, intrinsic safety, wired interlocks, maintenance, troubleshooting, and asset management. 

In the control room, process control encompasses the selection and installation of panel-mounted alarms, switches, recorders, and controllers, as well as Program Logic Controllers (PLC) and Distributed Control Systems (DCS). These include analog and digital input/output hardware, software to implement control strategies. 

the design practice includes P ID documentation, database specification and verification of purchased equipment, control design and performance analysis, software configuration, real-time simulation for DCS system checkout and operator training, reliability studies, interlock classification and risk assessment of safety instrumented systems (SIS), and hazard and operability (HAZOP) studies. 

Books have been written about each of these sub-topics and many standards exist to specify best practices or provide guidance. The Instrumentation, Systems and Automation Society (ISA) is the primary professional society that addresses many of these different aspects of process control. The focus of this chapter will be on control loop principles, loop tuning, and basic control strategies for continuous processes. 

In the past because melts have different properties and there were many ways to control processes, compared to what has happened, it was difficult to interrelate them. Detailed factual predictions of final output were rather difficult to arrive prior to prototyping, fabricating, or 

Regardless of the PC available or used, the molder setting up the process uses a systematic approach that should be outlined. Once the system is operating, the processor methodically makes one change at a time to set up the most efficient operation. 

Many devices are available for PC, such as pressure and temperature sensors, actuators, or computer programs, which can be used by the molder. These devices can be connected with the automation apparatus and integrated into a procedure. 

Mathematical models are used for these purposes in the plastic/ chemical, petrochemical, and other industries. Computer-aided design (CAD), computer-aided manufacturing (CAM) are use in product designs and product manufacturing operations. The essential elements of any model of a physical process are threefold the geometry, the relevant laws of physical conservation (momentum, mass, and energy), and the specific constitutive relations (see the Software section in Chapter 9). 

The manufactiuing processes offer great flexibility for creating a wide range of RP products. Recent years have seen a growth in PCs software 

Automatic feedback control is the continuous or repetitive modification of some operating parameters based on measurement data. Due to the dynamic nature of the process, the control algorithm is usually also dynamic and has to be designed carefully to avoid instability. We have to distinguish between two types of process control standard and advanced one. Standard controllers have a static algorithm like PID-controller type or cascade mode for the temperature control. Advanced control schemes use a more sophisticated algorithm that could be based on shortcut models or dynamic process models. 

II processes are subject to disturbances that tend to change operating conditions, compositions, and physical properties of the streams. In order to minimize the ill effects that could result from such disturbances, chemical plants are implemented with substantial amounts of instrumentation and automatic control equipment. In critical cases and in especially large plants, moreover, the instrumentation is computer monitored for convenience, safety, and optimization. 

In order for a process to be controllable by machine, it must represented by a mathematical mode/. Ideally, each element of a dynamic process, for example, a reflux drum or 

Two main control schemes exist feedback control and feed-forward control (Fig. 6). In feedback control (by far the most common), system performance is monitored, deviations from desired conditions are quantified, and controlled variables are modified to return the system to the desired state. In feed-forward control, process inputs are monitored. As they deviate from desired values, their effect on the system is predicted, and controlled variables are modified to minimize their effect. Feedback control is safer, since it guarantees performance by controlling it directly, but it is also slower corrective action is taken only after the perturbation has affected process performance. Feed-forward control is faster it acts on input deviations as soon as they are detected. However, it is riskier if the detected 

It is apparent that a predictive model is the hearth a control algorithm. Unless the relationship between process inputs and process performance is known, deviations can be detected, but effective corrective action cannot be taken. However, fast, error-free monitoring is also essential unless inputs and state variables can be quickly and accurately quantified, the control system is blind and devoid of value. 

As with scale-up, two levels of implementation are possible. The first level only entails the ability to sense, and a directional characterization of the effect of variables. PAT methods can be extremely effective for this purpose by generating large datasets of process inputs and outputs that can then be correlated to generate statistical or polynomial control models. Provided that (i) deviations from desired set-points are small, (ii) interactions between inputs are weak, and (Hi) the response surface does not depart too much from linearity, such systems can provide the basis of an initial effort to control a system. 

However, for many systems, more sophisticated control systems capable of overcoming these restrictions are likely to be desirable. To develop such systems, we need to expand the predictive models mentioned above to incorporate the dynamic effects of input, control, and process variables. The model needs to be able to answer questions such as how quickly do deviations in input conditions propagate through the system, how does the system respond over time under different control policies, and what is the 

Arguably, given its immediate and direct impact on public health, the pharmaceutical industry has additional reasons to achieve a higher level of technological execution where product quality is assured by effective automated systems and where variability sources are understood and minimized. Even removing this motivation, this industry should embrace model-based optimization enthusiastically, since it has reduced cost and accelerated product development across many other industries. 

Many of the inherently safer design aspects discussed here appear in Guidelines for Safe Automation of Chemical Processes (CCPS, 1993b). It makes excellent reading for greater depth and treatment of inherently safer/process control concepts. 

The ultimate goal of inherently safer design is elimination of all hazards with no need for controls. However, some control systems are always required. The working logic of a specific control system can make it inherently safer than other alternatives. 

Design and development of inherently safer process chemistry and physical treatment may be the most economical way to eliminate a 

For such a tank, the maximum setpoint for the level must be reduced to allow adequate response time. 

For some processes, human intervention is included in the response to an upset. See Section 6.5 for a discussion of the human response time in process control. 

The entire system is based on a tiered approach where three layers of technology are integrated into the overall treatment system, as illustrated in Chart 2. First, a distributed process control system is network linked to the various component subunits of the waste management system such as pH control, ion-exchange control, tank level control, etc. Next, are the recovery/treatment processes themselves. The final tier is a monitoring system which controls both the performance of the treatment systems and the discharge assurance of the plant effluent 

This approach makes the system simple to operate. The entire process is automatically monitored, recorded, and controlled. Operators can run the system from the central console, or from the local control units. And because of the distributed control, each of the local units will continue to do its job, and the waste treatment system will continue to function, even if the central control unit should became disconnected or malfunction. The system also includes a modem for remote diagnostics and program maintenance. 

Network Distributed Process Control System (links treatment system components to central monitor station) 

Selective Recovery Process for Segregated Waste Stream (use of synergistic combination of technologies) 

Process Monitoring and Discharge Control (Online chemical analyzers monitor recovery process performance and effluent prior to discharge) 

The aim of the factory production is to produce, as economically as possible, a consistent product with the specified properties. The key points in achieving this are  

Instantaneous heat rise on mixing isocyanates and diols. 

A set procedure for each grade must be set up and strictly adhered to. For normal quality assurance, the weights, temperatures, and times must be logged. The degree of sophistication of each plant can vary from a purely manual system to a computer-controlled, fully automated unit. 

Temperature control is normally carried out using thermocouples in a stainless steel pocket. The type of thermocouple used is either a platinum resistance detector (RTD) or a thermocouple using two dissimilar metals that produce a voltage (EMF). The indicators for these thermocouples must match the probe type and grade. The positioning of the probes is very important as well as any lag (delay) in the system. The output from the probe is connected to the indicator and/or controllers. Most indicators have at least a set point with an on/off output. The more advanced units will allow anticipated switching, more than one set point, temperature ramping between temperatures, time, and hold facilities. Thermocouple break and over-temperature alarm outputs are also commonly provided features. 

The output from the temperature controller can be fed into control valves, either on/off or proportional, or into a PLC, which can be programmed to turn off the polyol feed and heat and start the cooling cycle. 

To be effective, the perturbations should be sufficiently small that the product is always of an acceptable quality yet sufficiently large that meaningful comparisons can be made between the different conditions. 

The following sensor systems can be used for monitoring resin flow and/or 

The gasifier load reduction (approximately 60% of the nominal load) is limited by the minimum entrainment velocity of fresh fuel above the moving bed and the minimmn oxygen velocity in the nozzles. The carbon holdup of the fluid-bed section is expected to provide safety times for oxygen breakthrough in case of fuel outages of more than 10 s. Because of the water wall, start-up and shutdown times are not limited by refractory behavior. 

Consumption for maximum cold gas efficiency (---) and maximum syngas yield (-----) 

Alternatively, a full water quench on the raw gas can combine robust gas cooling and bulk dust removal in one step. The mixture of excess water and fly ash can be partly dewatered and sent back into the reaction chamber as slurry. 

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SMITH, VAN LAAN Piping and Pipe Support Systems STOCK AI in Process Control... 

Because of their widespread use for simple process control, hydrometers are frequently calibrated, not in specific gravity, but in some units related to it, which bear (or bore at one time) some relationship to the concentration being so measured. 

The modem era of biochemistry and molecular biology has been shaped not least by the isolation and characterization of individual molecules. Recently, however, more and more polyfunctional macromolecular complexes are being discovered, including nonrandomly codistributed membrane-bound proteins [41], These are made up of several individual proteins, which can assemble spontaneously, possibly in the presence of a lipid membrane or an element of the cytoskeleton [42] which are themselves supramolecular complexes. Some of these complexes, e.g. snail haemocyanin [4o], are merely assembled from a very large number of identical subunits vimses are much larger and more elaborate and we are still some way from understanding the processes controlling the assembly of the wonderfully intricate and beautiful stmctures responsible for the iridescent colours of butterflies and moths [44]. 

ANHBIOHCS - GLYCOPEPTIDES (DALBAHEPTIDES)] (Vol 2) -food processing control pOOD PROCESSING] (Vol 11)... 

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