Process Control Automation Instrumentation And Scada Pdf

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A distributed control system DCS is a computerised control system for a process or plant usually with many control loops , in which autonomous controllers are distributed throughout the system, but there is no central operator supervisory control. This is in contrast to systems that use centralized controllers; either discrete controllers located at a central control room or within a central computer. The DCS concept increases reliability and reduces installation costs by localising control functions near the process plant, with remote monitoring and supervision.

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Industrial Process Automation Systems: Design and Implementation is a clear guide to the practicalities of modern industrial automation systems. Bridging the gap between theory and technician-level coverage, it offers a pragmatic approach to the subject based on industrial experience, taking in the latest technologies and professional practices. Practicing automation design and maintenance engineers, junior level engineers from instrumentation, electrical, chemical and production. Students at PG level for Control and Instrumentation, Process Automation, Chemical Engineering in chemical, petrochemical, power, metals, mining and pharmaceutical industries. During his career he has worked with many overseas licensors, including U.

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A distributed control system DCS is a computerised control system for a process or plant usually with many control loops , in which autonomous controllers are distributed throughout the system, but there is no central operator supervisory control. This is in contrast to systems that use centralized controllers; either discrete controllers located at a central control room or within a central computer.

The DCS concept increases reliability and reduces installation costs by localising control functions near the process plant, with remote monitoring and supervision.

Distributed control systems first emerged in large, high value, safety critical process industries, and were attractive because the DCS manufacturer would supply both the local control level and central supervisory equipment as an integrated package, thus reducing design integration risk. Today the functionality of SCADA and DCS systems are very similar, but DCS tends to be used on large continuous process plants where high reliability and security is important, and the control room is not geographically remote.

The key attribute of a DCS is its reliability due to the distribution of the control processing around nodes in the system. This mitigates a single processor failure. If a processor fails, it will only affect one section of the plant process, as opposed to a failure of a central computer which would affect the whole process. The accompanying diagram is a general model which shows functional manufacturing levels using computerised control.

Levels 1 and 2 are the functional levels of a traditional DCS, in which all equipment are part of an integrated system from a single manufacturer. Levels 3 and 4 are not strictly process control in the traditional sense, but where production control and scheduling takes place. The processor nodes and operator graphical displays are connected over proprietary or industry standard networks, and network reliability is increased by dual redundancy cabling over diverse routes.

The processors receive information from input modules, process the information and decide control actions to be signalled by the output modules. The field inputs and outputs can be analog signals e. DCSs are connected to sensors and actuators and use setpoint control to control the flow of material through the plant.

A typical application is a PID controller fed by a flow meter and using a control valve as the final control element. The DCS sends the setpoint required by the process to the controller which instructs a valve to operate so that the process reaches and stays at the desired setpoint. Processes are not limited to fluidic flow through pipes, however, and can also include things like paper machines and their associated quality controls, variable speed drives and motor control centers , cement kilns , mining operations , ore processing facilities, and many others.

DCSs in very high reliability applications can have dual redundant processors with "hot" switch over on fault, to enhance the reliability of the control system.

Modern DCSs also support neural networks and fuzzy logic applications. Recent research focuses on the synthesis of optimal distributed controllers, which optimizes a certain H-infinity or the H 2 control criterion.

Distributed control systems DCS are dedicated systems used in manufacturing processes that are continuous or batch-oriented. Process control of large industrial plants has evolved through many stages.

Initially, control would be from panels local to the process plant. However this required a large manpower resource to attend to these dispersed panels, and there was no overall view of the process.

The next logical development was the transmission of all plant measurements to a permanently-manned central control room. Effectively this was the centralisation of all the localised panels, with the advantages of lower manning levels and easier overview of the process.

Often the controllers were behind the control room panels, and all automatic and manual control outputs were transmitted back to plant. However, whilst providing a central control focus, this arrangement was inflexible as each control loop had its own controller hardware, and continual operator movement within the control room was required to view different parts of the process. These could be distributed around plant, and communicate with the graphic display in the control room or rooms.

The distributed control system was born. The introduction of DCSs allowed easy interconnection and re-configuration of plant controls such as cascaded loops and interlocks, and easy interfacing with other production computer systems.

It enabled sophisticated alarm handling, introduced automatic event logging, removed the need for physical records such as chart recorders, allowed the control racks to be networked and thereby located locally to plant to reduce cabling runs, and provided high level overviews of plant status and production levels.

Early minicomputers were used in the control of industrial processes since the beginning of the s. The DCS largely came about due to the increased availability of microcomputers and the proliferation of microprocessors in the world of process control. Computers had already been applied to process automation for some time in the form of both direct digital control DDC and setpoint control. Sophisticated for the time continuous as well as batch control was implemented in this way. A more conservative approach was setpoint control, where process computers supervised clusters of analog process controllers.

A workstation provided visibility into the process using text and crude character graphics. Availability of a fully functional graphical user interface was a way away. Central to the DCS model was the inclusion of control function blocks. One of the first embodiments of object-oriented software, function blocks were self-contained "blocks" of code that emulated analog hardware control components and performed tasks that were essential to process control, such as execution of PID algorithms.

Function blocks continue to endure as the predominant method of control for DCS suppliers, and are supported by key technologies such as Foundation Fieldbus [7] today.

Midac Systems, of Sydney, Australia, developed an objected-oriented distributed direct digital control system in The central system ran 11 microprocessors sharing tasks and common memory and connected to a serial communication network of distributed controllers each running two Z80s. The system was installed at the University of Melbourne. Digital communication between distributed controllers, workstations and other computing elements peer to peer access was one of the primary advantages of the DCS.

Attention was duly focused on the networks, which provided the all-important lines of communication that, for process applications, had to incorporate specific functions such as determinism and redundancy. As a result, many suppliers embraced the IEEE This decision set the stage for the wave of migrations necessary when information technology moved into process automation and IEEE In the s, users began to look at DCSs as more than just basic process control.

The system installed at the University of Melbourne used a serial communications network, connecting campus buildings back to a control room "front end". Each remote unit ran two Z80 microprocessors, while the front end ran eleven Z80s in a parallel processing configuration with paged common memory to share tasks and that could run up to 20, concurrent control objects. It was believed that if openness could be achieved and greater amounts of data could be shared throughout the enterprise that even greater things could be achieved.

As a result, suppliers also began to adopt Ethernet-based networks with their own proprietary protocol layers. Plant-wide historians also emerged to capitalize on the extended reach of automation systems. The drive toward openness in the s gained momentum through the s with the increased adoption of commercial off-the-shelf COTS components and IT standards.

Probably the biggest transition undertaken during this time was the move from the UNIX operating system to the Windows environment. While the realm of the real time operating system RTOS for control applications remains dominated by real time commercial variants of UNIX or proprietary operating systems, everything above real-time control has made the transition to Windows.

The introduction of Microsoft at the desktop and server layers resulted in the development of technologies such as OLE for process control OPC , which is now a de facto industry connectivity standard. The s were also known for the "Fieldbus Wars", where rival organizations competed to define what would become the IEC fieldbus standard for digital communication with field instrumentation instead of 4—20 milliamp analog communications. The first fieldbus installations occurred in the s.

Fieldbus technics have been used to integrate machine, drives, quality and condition monitoring applications to one DCS with Valmet DNA system. The impact of COTS, however, was most pronounced at the hardware layer. The initial proliferation of DCSs required the installation of prodigious amounts of this hardware, most of it manufactured from the bottom up by DCS suppliers. Standard computer components from manufacturers such as Intel and Motorola, however, made it cost prohibitive for DCS suppliers to continue making their own components, workstations, and networking hardware.

As the suppliers made the transition to COTS components, they also discovered that the hardware market was shrinking fast. COTS not only resulted in lower manufacturing costs for the supplier, but also steadily decreasing prices for the end users, who were also becoming increasingly vocal over what they perceived to be unduly high hardware costs. The gaps among the various systems remain at the areas such as: the database integrity, pre-engineering functionality, system maturity, communication transparency and reliability.

While it is expected the cost ratio is relatively the same the more powerful the systems are, the more expensive they will be , the reality of the automation business is often operating strategically case by case. The current next evolution step is called Collaborative Process Automation Systems.

To compound the issue, suppliers were also realizing that the hardware market was becoming saturated. Many of the older systems that were installed in the s and s are still in use today, and there is a considerable installed base of systems in the market that are approaching the end of their useful life.

Developed industrial economies in North America, Europe, and Japan already had many thousands of DCSs installed, and with few if any new plants being built, the market for new hardware was shifting rapidly to smaller, albeit faster growing regions such as China, Latin America, and Eastern Europe.

Because of the shrinking hardware business, suppliers began to make the challenging transition from a hardware-based business model to one based on software and value-added services. It is a transition that is still being made today. The applications portfolio offered by suppliers expanded considerably in the '90s to include areas such as production management, model-based control, real-time optimization, plant asset management PAM , Real-time performance management RPM tools, alarm management , and many others.

To obtain the true value from these applications, however, often requires a considerable service content, which the suppliers also provide.

Increasingly, and ironically, DCS are becoming centralised at plant level, with the ability to log into the remote equipment. This enables operator to control both at enterprise level macro and at the equipment level micro , both within and outside the plant, because the importance of the physical location drops due to interconnectivity primarily thanks to wireless and remote access.

The more wireless protocols are developed and refined, the more they are included in DCS. DCS controllers are now often equipped with embedded servers and provide on-the-go web access. With these interfaces, the threat of security breaches and possible damage to plant and process are now very real. From Wikipedia, the free encyclopedia. Computerized control systems with distributed decision-making.

Archived from the original on Retrieved Foukalas and P. Pop, " Distributed control plane for safe cooperative vehicular cyber physical systems. Categories : Control engineering Applications of distributed computing Industrial automation. Hidden categories: CS1 maint: archived copy as title Use British English from February Articles with short description Short description is different from Wikidata All articles with unsourced statements Articles with unsourced statements from August Namespaces Article Talk.

Views Read Edit View history. Help Learn to edit Community portal Recent changes Upload file. Download as PDF Printable version. Part of a series of articles on. Batch production Job production Flow production Lean manufacturing Agile manufacturing.

Industrial Process Automation Systems

Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. The idea behind this work is to replace the conventional PID controller available in the level control trainer system with a high end Programmable Logic Controller. The motive behind doing this is to obtain a complete understanding of the changes in the dynamics of the system and transient response characteristics associated with the system. Mathematical model is obtained for the actual system using the mass-balance formulas and the same model is validated.

Process control systems PCS , sometimes called industrial control systems ICS , function as pieces of equipment along the production line during manufacturing that test the process in a variety of ways, and return data for monitoring and troubleshooting. Many types of process control systems exist, including supervisory control and data acquisition SCADA , programmable logic controllers PLC , or distributed control systems DCS , and they work to gather and transmit data obtained during the manufacturing process. The PCS can be a relatively simple item with a sensor, often called a primary transducer, that receives an input, along with a controller that processes the input, and a receiver that processes an output. More complicated PCS devices are robotic and perform many tasks. A great number of measurements can be taken on production lines. An equipment's sensor can pick up many measurements including pressure, flow rate, density, acidity, velocity, speed, stress, temperature, and weight. Also, sensors can detect if an operation has occurred, such as the fill of a bottle, whether the correct pressure has been achieved, or if a certain temperature has been reached.

industrial control system that consists of instrumentation, communications, PLC automation equipment, and human machine interface (HMI) computer systems.

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Hardware Architecture which is created for ideal material calcination and applied Software are inseperable whole of each other. The implemented software has sophisticated structure. It is the control structure of solid material dosing and mixing facilities which are performed prescription-based production. It is prepared by considering the requirements of production reporting of facilities and need for creation of prescription records. Gersan Sanayi Sitesi Sok.

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Supervisory control and data acquisition SCADA is a control system architecture comprising computers , networked data communications and graphical user interfaces GUI for high-level process supervisory management, while also comprising other peripheral devices like programmable logic controllers PLC and discrete proportional-integral-derivative PID controllers to interface with process plant or machinery. The use of SCADA has been considered also for management and operations of project-driven-process in construction. The operator interfaces which enable monitoring and the issuing of process commands, like controller set point changes, are handled through the SCADA computer system. The subordinated operations, e. The SCADA concept was developed to be a universal means of remote-access to a variety of local control modules, which could be from different manufacturers and allowing access through standard automation protocols. In practice, large SCADA systems have grown to become very similar to distributed control systems in function, while using multiple means of interfacing with the plant.

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    Instrumentation. • mA Industrial Automation. Definitions. • SCADA. – Supervisory Control and Data keep logs on the operation of the automation system.