A chemical plant is an industrial process plant that manufactures chemicals on a large scale. The general objective of a chemical plant is to create new material wealth via the chemical or biological transformation and or separation of materials. Chemical plants use specialized equipment and technology in the manufacturing process. Other kinds of plants, such as polymer, pharmaceutical and some beverage production facilities, power plants, oil refineries or other refineries, natural gas processing and biochemical plants and wastewater treatment, pollution control equipment use many technologies that have similarities to chemical plant technology such as fluid systems and chemical reactor systems; some would consider an oil refinery or a pharmaceutical or polymer manufacturer to be a chemical plant. Petrochemical plants are located adjacent to an oil refinery to minimize transportation costs for the feedstocks produced by the refinery. Speciality chemical and fine chemical plants are much smaller and not as sensitive to location.
Tools have been developed for converting a base project cost from one geographic location to another. Chemical plants use chemical processes, which are detailed industrial-scale methods, to transform feedstock chemicals into products; the same chemical process can be used at more than one chemical plant, with differently scaled capacities at each plant. A chemical plant at a site may be constructed to utilize more than one chemical process, for instance to produce multiple products. A chemical plant has large vessels or sections called units or lines that are interconnected by piping or other material-moving equipment which can carry streams of material; such material streams can include fluids or sometimes mixtures such as slurries. An overall chemical process is made up of steps called unit operations which occur in the individual units. A raw material going into a chemical process or plant as input to be converted into a product is called a feedstock, or feed. In addition to feedstocks for the plant as a whole, an input stream of material to be processed in a particular unit can be considered feed for that unit.
Output streams from the plant as a whole are final products and sometimes output streams from individual units may be considered intermediate products for their units. However, final products from one plant may be intermediate chemicals used as feedstock in another plant for further processing. For example, some products from an oil refinery may used as feedstock in petrochemical plants, which may in turn produce feedstocks for pharmaceutical plants. Either the feedstock, the product, or both may be individual mixtures, it is not worthwhile separating the components in these mixtures completely. Chemical processes may be run in batch operation. In batch operation, production occurs in time-sequential steps in discrete batches. A batch of feedstock is fed into a process or unit the chemical process takes place the product and any other outputs are removed; such batch production may be repeated over again with new batches of feedstock. Batch operation is used in smaller scale plants such as pharmaceutical or specialty chemicals production, for purposes of improved traceability as well as flexibility.
Continuous plants are used to manufacture commodity or petrochemicals while batch plants are more common in speciality and fine chemical production as well as pharmaceutical active ingredient manufacture. In continuous operation, all steps are ongoing continuously in time. During usual continuous operation, the feeding and product removal are ongoing streams of moving material, which together with the process itself, all take place and continuously. Chemical plants or units in continuous operation are in a steady state or approximate steady state. Steady state means that quantities related to the process do not change as time passes during operation; such constant quantities include stream flow rates, heating or cooling rates, temperatures and chemical compositions at any given point. Continuous operation is more efficient in many large scale operations like petroleum refineries, it is possible for some units to operate continuously and others be in batch operation in a chemical plant. The amount of primary feedstock or product per unit of time which a plant or unit can process is referred to as the capacity of that plant or unit.
For examples: the capacity of an oil refinery may be given in terms of barrels of crude oil refined per day. In actual daily operation, a plant will operate at a percentage of its full capacity. Engineers assume 90% operating time for plants which work with fluids, 80% uptime for plants which work with solids. Specific unit operations are conducted in specific kinds of units. Although some units may operate at ambient temperature or pressure, many units operate at higher or lower temperatures or pressures. Vessels in chemical plants are cylindrical with rounded ends, a shape which can be suited to hold either high pressure or vacuum. Chemical reactions can convert certain kinds of compounds into other compounds in chemical reactors. Chemical reactors may be packed beds and may have solid heterogeneous catalysts which stay in the r
Process simulation is used for the design, development and optimization of technical processes such as: chemical plants, chemical processes, environmental systems, power stations, complex manufacturing operations, biological processes, similar technical functions. Process simulation is a model-based representation of chemical, physical and other technical processes and unit operations in software. Basic prerequisites are a thorough knowledge of chemical and physical properties of pure components and mixtures, of reactions, of mathematical models which, in combination, allow the calculation of a process in computers. Process simulation software describes processes in flow diagrams where unit operations are positioned and connected by product or educt streams; the software has to solve the energy balance to find a stable operating point. The goal of a process simulation is to find optimal conditions for an examined process; this is an optimization problem which has to be solved in an iterative process.
Process simulation always use models which introduce approximations and assumptions but allow the description of a property over a wide range of temperatures and pressures which might not be covered by real data. Models allow interpolation and extrapolation - within certain limits - and enable the search for conditions outside the range of known properties; the development of models for a better representation of real processes is the core of the further development of the simulation software. Model development is done on the chemical engineering side but in control engineering and for the improvement of mathematical simulation techniques. Process simulation is therefore one of the few fields where scientists from chemistry, computer science and several engineering fields work together. A lot of efforts are made to develop improved models for the calculation of properties; this includes for example the description of thermophysical properties like vapor pressures, caloric data, etc. of pure components and mixtures properties of different apparatuses like reactors, distillation columns, etc. chemical reactions and kinetics environmental and safety-related dataTwo main different types of models can be distinguished: Rather simple equations and correlations where parameters are fitted to experimental data.
Predictive methods where properties are estimated. The equations and correlations are preferred because they describe the property exactly. To obtain reliable parameters it is necessary to have experimental data which are obtained from factual data banks or, if no data are publicly available, from measurements. Using predictive methods is much cheaper than experimental work and than data from data banks. Despite this big advantage predicted properties are only used in early steps of the process development to find first approximate solutions and to exclude wrong pathways because these estimation methods introduce higher errors than correlations obtained from real data. Process simulation encouraged the further development of mathematical models in the fields of numerics and the solving of complex problems; the history of process simulation is related to the development of the computer science and of computer hardware and programming languages. Early working simple implementations of partial aspects of chemical processes were introduced in the 1970s when suitable hardware and software became available.
The modelling of chemical properties began much earlier, notably the cubic equation of states and the Antoine equation were precursory developments of the 19th century. Process simulation was used to simulate steady state processes. Steady-state models perform a mass and energy balance of a stationary process it does not depend on time. Dynamic simulation is an extension of steady-state process simulation whereby time-dependence is built into the models via derivative terms i.e. accumulation of mass and energy. The advent of dynamic simulation means that the time-dependent description and control of real processes in real time has become possible; this includes the description of starting up and shutting down a plant, changes of conditions during a reaction, thermal changes and more. Dynamic simulations require increased calculation time and are mathematically more complex than a steady state simulation, it can be seen as a multiply repeated steady state simulation with changing parameters. Dynamic simulation can be used in both an offline fashion.
The online case being model predictive control, where the real-time simulation results are used to predict the changes that would occur for a control input change, the control parameters are optimised based on the results. Offline process simulation can be used in the design and optimisation of process plant as well as the conduction of case studies to assess the impacts of process modifications. Dynamic simulation is used for operator training. Advanced Simulation Library Computer simulation List of chemical process simulators Software Process simulation
A control loop is the fundamental building block of industrial control systems. It consists of all the physical components and control functions necessary to automatically adjust the value of a measured process variable to equal the value of a desired set-point, it includes the process sensor, the controller function, the final control element which are all required for automatic control. The accompanying diagram shows a control loop with a single PV input, a control function, the control output which modulates the action of the final control element to alter the value of the manipulated variable. In this example, a flow control loop is shown, but can be level, temperature, or any one of many process parameters which need to be controlled; the control function shown is an "intermediate type" such as a PID controller which means it can generate a full range of output signals anywhere between 0-100%, rather than just an on/off signal. In this example the value of the PV is always the same as the MV, as they are in series in the pipeline.
However, if the feed from the valve was to a tank, the controller function was to control level using the fill valve, the PV would be the tank level, the MV would be the flow to the tank. The controller function can be a discrete controller, or a function block in a computerised control system such as a distributed control system or a programmable logic controller. In all cases, a control loop diagram is a convenient and useful way of representing the control function and its interaction with plant. In practice at a process control level, the control loops are abbreviated using standard symbols in a Piping and instrumentation diagram, which shows all elements of the process measurement and control based on a process flow diagram. At a detailed level the control loop connection diagram is created to show the electrical and pneumatic connections; this aids diagnostics and repair, as all the connections for a single control function are on one diagram. To aid unique identification of equipment, each loop and its elements are identified by a "tagging" system and each element has a unique tag identification.
Based on the standards ANSI/ISA S5.1 and ISO 14617-6, the identifications consist of up to 5 letters. The first identification letter is for the measured value, the second is a modifier, 3rd indicates passive/readout function, 4th - active/output function, the 5th is the function modifier; this is followed by loop number, unique to that loop. For instance FIC045 means it is the Flow Indicating Controller in control loop 045; this is known as the "tag" identifier of the field device, given to the location and function of the instrument. The same loop may have FT045 -, the flow transmitter in the same loop. For reference designation of any equipment in industrial systems the standard IEC 61346 (Industrial systems and equipment and industrial products — Structuring principles and reference