Process Algoritma

The General Control System

2012-01-04T05:46:00.000-08:00

A process is shown in Fig. 8-1 with a manipulated input M, a load input L, and a controlled output C, which could be flow, pressure, liquid level, temperature, composition, or any other inventory, environmental, or quality variable that is to be held at a desired value identified as the set point R. The load may be a single variable or aggregate of variables acting either independently or manipulated for other purposes, affecting the controlled variable much as the manipulated variable does. Changes in load may occur randomly as caused by changes in weather, diurnally with ambient temperature, manually when operators change production rate, stepwise when equipment is switched in or out of service, or cyclically as the result of oscillations in other control loops. Variations in load will drive the controlled variable away from set point, requiring a corresponding change in the manipulated variable to bring it back. The manipulated variable must also change to move the controlled variable from one set point to another. An open-loop system positions the manipulated variable either manually or on a programmed basis, without using any process measurements.

This operation is acceptable for well-defined processes without disturbances. An auto manual transfer switch is provided to allow manual adjustment of the manipulated variable in case the process or the control system is not performing satisfactorily.

A closed-loop system uses the measurement of one or more process variables to move the manipulated variable to achieve control. Closed-loop systems may include feed-forward, feedback, or both. Feedback Control In a feedback control loop, the controlled variable is compared to the set point R, with the difference, deviation, or error e acted upon by the controller to move m in such a way as to minimize the error. This action is specifically negative feedback, in that an increase in deviation moves m so as to decrease the deviation. (Positive feedback would cause the deviation to expand rather than diminish and therefore does not regulate.) The action of the controller is selectable to allow use on process gains of both signs.

The controller has tuning parameters related to proportional, integral, derivative, lag, dead time, and sampling functions. A negative feedback loop will oscillate if the controller gain is too high, but if it is too low, control will be ineffective. The controller parameters must be properly related to the process parameters to ensure closed-loop stability while still providing effective control. This is accomplished first by the proper selection of control modes to satisfy the requirements of the process, and second by the appropriate tuning of those modes.

Feed-forward Control A feed-forward system uses measurements of disturbance variables to position the manipulated variable in variables could be either measured loads or the set point, the former being more common. The feed-forward gain must be set precisely to offset the deviation of the controlled variable from the set point.

Feed-forward control is usually combined with feedback control to eliminate any offset resulting from inaccurate measurements and calculations and unmeasured load components. The feedback controller can either bias or multiply the feed-forward calculation.

Computer Control Computers have been used to replace analog PID controllers, either by setting set points of lower level controllers in supervisory control, or by driving valves directly in direct digital control. Single-station digital controllers perform PID control in one or two loops, including computing functions such as mathematical operations, characterization, lags, and dead time, with digital logic and alarms. Distributed control systems provide all these functions, with the digital processor shared among many control loops; separate processors may be used for displays, communications, file servers, and the like. A host computer may be added to perform high level operations such as scheduling, optimization, and multi variable control. More details on computer control are provided later in this section.

Process Dynamic and Mathematical Model

GENERAL REFERENCES: Seborg, Edgar, and Mellichamp, Process Dynamics and Control, Wiley, New York, 1989; Marlin, Process Control, McGraw-Hill, New York, 1995; Ogunnaike and Ray, Process Dynamics Modeling and Control, Oxford University Press, New York, 1994; Smith and Corripio, Principles and Practices of Automatic Process Control, Wiley, New York, 1985 Open-Loop versus Closed-Loop Dynamics It is common in industry to manipulate coolant in a jacketed reactor in order to control conditions in the reactor itself. A simplified schematic diagram of such a reactor control system is shown in Fig. 8-2.

Assume that the reactor temperature is adjusted by a controller that increases the coolant flow in proportion to the difference between the desired reactor temperature and the temperature that is measured. The proportionality constant is Kc. If a small change in the temperature of the inlet stream occurs, then depending on the value of Kc, one might observe the reactor temperature responses shown in Fig. 8-3. The top plot shows the case for no control (Kc = 0), which is called the open loop, or the normal dynamic response of the process by itself. As Kc increases, several effects can be noted. First, the reactor temperature responds faster and faster. Second, for the initial increases in Kc, the maximum deviation in the reactor temperature becomes smaller. Both of these effects are desirable so that disturbances from normal operation have as small an effect as possible on the process under study. As the gain is increased further, eventually a point is reached where the reactor temperature oscillates indefinitely, which is undesirable. This point is called the stability limit, where

Kc = Ku, the ultimate controller gain.

Increasing Kc further causes the magnitude of the oscillations to increase, with the result that the control valve will cycle between full open and closed. The responses shown in Fig. 8-3 are typical of the vast majority of regulatory loops encountered in the process industries. Figure 8-3 shows that there is an optimal choice for Kc, somewhere between 0 (no control) and Ku (stability limit). If one has a dynamic model of a process, then this model can be used to calculate controller settings.

In Fig. 8-3, no time scale is given, but rather the figure shows relative responses. A well-designed controller might be able to speed up the response of a process by a factor of roughly two to four. Exactly how fast the control system responds is determined by the dynamics of the process itself.

Communication Cycle

2011-12-26T01:13:00.000-08:00

A medium communication is a system that enables the flow of messages between one or more creators of messages and one or more receivers of messages. The range of media therefore includes such simple systems as face to face communication, in which human modalities, light, and air are all that is necessary to enable communication and such complex media as television, in which a broad range of intermediate elements are used as a system to route messages from a small number of message creators to a large number of message consumers.

New communication media are invented in five interrelated "spheres" of invention as shown in the picture: mediators, characteristics, uses, effects, and practices. The “invention” of a medium entails invention activity in all of these spheres, with changes any one sphere provoking activity in others. The most common paths for such provocations are shown as the Cycle of Media and Cycle of Genre in the above picture.

Mediators are the fundamental building blocks of media, and include (using the telephone as an example) such things as telephones, telephone wires, telephone switches, operators, and billing systems. All media entail mediators. Even face-to-face communication depends on human modalities and the natural resources (air and light) that allow them to function. New media are built in the sphere of mediators, with resources (including technologies and people) organized (in structure and process) to support the creation and consumption of messages.

Algoritmic Trading

2011-11-29T15:27:00.000-08:00

Algoritmic trading is the term used in the electronic financial markets. Algoritmic trading also known as automated trading, or called as algo trading, black-box trading or robo trading. By this system people just use electronic platforms for entering trading orders with algorthm deciding the spect of order such as timing, price, or quantity of order, or other many cases initiating order without human intervention.

This system often used by pension funds, mutual funds, and other buy side institutional traders, to devide large trades into several smaller trades in order to manage market impact, and risk. Sell side traders, such as market makers and some hedge fungs, provide liquidity to the market, generating and executing orders automatically.

Algoritmic trading may be used in any investment strategy, including market making, intermarket spreading, arbitrage, or pure speculation (including trend following). Investment decision and implementation may be augmented at any stage with algoritmic support or may operate completely automatically.

Radioactive Handling Procedure

2011-10-27T08:09:00.000-07:00

Radioactive waste is the radioactive substance and the equipment or apparatus that contaminated with radioactive material or become radioactive cause of nuclear installation that not used anymore.
Transport of Radioactive waste is the removal of radioactive waste from one place to other place through general traffic by means of land, water or air transportation.
Shipping is the process include technical and administrative preparation that done by waste producer followed by transport till accepted by PTLR.
Transporter is people or body that do waste transporting.
Packaging is package that contain of radioactive waste inside.
Sender is people or body that preparing of radioactive waste that stated on the waste document.
Receiver is PLTR

The flowchart of radioactive waste shipment handling as on the diagram below:

Pareto Diagram

2011-08-31T23:37:00.000-07:00

Pareto diagram is created by using their name Vitredo Pareto, a type of chart contain of bar and line graph. Individual value are represented in descending order by bars, and the cumulative total is represented by the line.

The purpose of pareto diagram is to highlight the most important among typically large set of factors in quality control, it often represents the most common sources of defects, the highest occurring type of defect, or the most frequent reasons for customer complaints, and so on. This chart can create simply by excel on Microsoft office or other software tools.

The sample of Pareto Diagram can see on the below graphic:

Pareto Diagram

Genetic Algoritm

2011-07-28T07:31:00.000-07:00

Genetic Algorithm is basically a computer program that simulates the evolutionary process. In this case the population of chromosomes is generated randomly and allowed to breed in accordance with the laws of evolution in hopes of producing an excellent individual chromosomes. These chromosomes are in fact the candidate solution of the problem, so that when the chromosomes are well developed, a good solution to the problem is expected to be generated.

Genetic algorithms are widely used in business applications, engineering and in scientific fields.This algorithm can be used to obtain a proper solution to the problem of optimal than one variable or multiple variables. Before the algorithm is run, what problems to be optimized it must be stated in the objective function, known as the fitness function. If the fitness value of the greater, then the system generated the better. Although at first all possible fitness values are very small (because these algorithms produce random), some will be higher than the other. Chromosomes with high fitness values will provide a high probability to reproduce the next generation. So for every generation in the evolutionary process, fitness function that simulates natural selection, will push the population towards an increased fitness.

Very precise genetic algorithm used for solving optimization problems are complex and difficult to be solved by using conventional methods. As the process of evolution in nature, a simple genetic algorithm generally consists of three operators: reproduction operator, crossover operator (crossover) and mutation carriers. The general structure of a genetic algorithm can be defined with the following steps:

Generating the initial population, initial population is generated randomly so we get the initial solutions. The population itself consists of a number of chromosomes that represent the desired solution.

Forming a new generation, used in forming the three operators mentioned above the carrier reproduction / selection, crossover and mutation. This process is done repeatedly so we get a sufficient number of chromosomes to form a new generation which is a representation of this new generation of new solutions.
Evaluation of the solution, this process will evaluate each population by calculating the fitness value of each chromosome and to evaluate it until the stop criteria are met. If the stop criteria have not been met then a new generation will be formed again by repeating step 2. Some stops are frequently used criteria include:

Stops at a certain generation.
Stopped after several successive generations obtained the highest fitness value does not change.
Stops when the next generation n not get a higher fitness value.

In the following description writers tried to discuss the application of genetic algorithms in the field of clean water distribution system, because during this time the author worked on a consultant in the field of water supply systems, and the author of mastering a bit about this issue.

Other Algorithm:

Heart Algorithmic

2011-05-11T06:54:00.000-07:00

Heart attack or heart diseases can causes by many problem like the effect of other disease that make the heart work abnormal. Some acute diabetes disease can make their heart get problem, contain of many cholesterol on our blood can make the heart block, but heart problem also can causes other many diseases that merge on their body so the main source itself sometime difficult to detect.

This effect can be reciprocally, so other diseases can cause heart disease and heart disease also make other diseases merge. The diagram of this diseases can be drawn simplify like as below:

So if we want have health body we must keep our body in balance in all the need. What are our body need? the need of our body is not just food, but also need education for our brain, need of appreciation, and need spiritual education. If this needs can be fulfill in balance then our body can get disease.

Virtual Networking

2011-03-26T05:43:00.000-07:00

Virtual PC are offer two mode of virtual networking. Both of those implemented on virtual DEC 21041 ethernal card.

Shared Networking
Share networking is useful for TCP/IP client connectivity. On this share is used NAT (network address translation) mechanism and DHCP server. Therefore share networking is work on TCP/IP level from stack networking, so this will compatible with all TCP/IP connection include of ethernet, token ring, dial up adapter (PPP) and so on. Shared networking is supported by protocol like IPX/SPX and NetBEUI.

The algorithm of this shared networking as follows:

Virtual Networking Algorithm

See other algorithm:

How to Create Algorithm From Scratch

2011-01-30T15:54:00.000-08:00

You can start to create your algorithm from scratch beginning from your basic thinking, from your start idea. You should write down what is your idea. Then you think what is your second stage and you should create arrow sign before you write down your idea or your next steps. The similar way you apply for your third step.

As the result you have your idea, for example like on the below diagram:

Create Pattern ===> Draw a Pattern on Paper ====> Cut the Paper

After you create your basic algorithm for something like to create or build or certain project or certain business, then you analyze your algorithm. May be after you think again your step diagram is wrong then you revise your diagram as your new idea. For example you apply Design first before Create Pattern on the above example.

Design Pattern ====> Create Pattern ===> Draw a Pattern on Paper ====> Cut the Paper

The pattern on the above diagram still on the paper, so if there is a mistake design, you can through away, and begin to create new design. For example on the above diagram you will form cut paper then you make new algorithm on the above diagram and then there are correction design if the formed is not right. Then you make your diagram as follows:

Computer System Algorithm

2010-08-28T10:18:00.000-07:00

Hardware:

Software: --------->

Brainware:

Control Principle

2010-08-19T20:22:00.001-07:00

Control of the process in the plant is an essential part of the plant operation. There must be enough water in the boilers to act as a heat sink for the reactor but there must not be water flowing out the top of the boilers towards the turbine. The level of the boiler must be kept within a certain range. The heat transport pressure is another critical parameter that must be controlled. If it is too high the system will burst, if it is too low the water will boil. Either condition impairs the ability of the heat transport system to cool the fuel.

In this section we will look at the very basics of control. We will examine the fundamental control building blocks of proportional, integral and differential and their application to some simple system.

Basic Control Principle
Consider a typical process control system. For a particular example let us look at an open tank, which supplies a process, say a pump, at its output. The tank will require a supply to maintain its level (and therefore the pump’s positive suction head) at a fixed predetermined point. This predetermined level is referred to as the setpoint (SP) and it is also the controlled quantity of the system.

Clearly whilst the inflow and outflow are in mass balance, the level will remain constant. Any different in the relative flows will cause the level to vary. How can we effectively control this system to a constant level? We must first identify our variables. Obviously there could be a number of variables in any system, the two in which we are most interested are:

- The controlled variable: in our example this will be level.
- The manipulated variable: the inflow and outflow from the system.

If we look more closely to the figure sample, assuming the level is at the setpoint, the inflow to the system and outflow are balanced, obviously no control action is required whilst this status quo exist. Control action is only necessary when a difference or error exists between the setpoint and the measured level. Depending on whether this error is a positive or negative quantity, the appropriate control correction will be made in an attempt to restore the process to the setpoint.

Henceforth, the error will always take the form of; Error = Setpoint – Measured Quantity or e = SP - M
The control action will be either to vary the inflow or outflow from the system in order to keep the level at the setpoint. Let us consider the general format for achieving this objective.

OHSAS Management System

2010-06-07T04:54:00.000-07:00

OHSAS Management system bases on standard methodology known as Plan – Do – Check and Action that can be briefly describe as follows:

Plan: establish the objectives and processes necessary to deliver results in accordance with the organization’s OH&S policy.
Do: implement the processes.
Check: monitor and measure processes against OH&S policy, objectives, legal and other requirements, and report the results.
Act: take actions to continually improve OH&S performance.

Many organizations manage their operations via the application of a system of processes and their interactions, which can be referred to as the “process approach”. ISO 9001 promotes the use of the process approach. Since PDCA can be applied to all processes, the two methodologies are considered to be compatible.

Create Diagram on Power Point

2010-02-18T06:57:00.000-08:00

You can draw a diagram or chart using Power Point. On the Drawing toolbar, click Diagram or Organizational Chart .

Click the Organization Chart diagram, and then click OK.
Do one or more of the following:
If you want to add text to a shape, right-click the shape, click Edit Text, and type the text.
Text cannot be added to lines or connectors in organization charts.

If you want to add a shape, select the shape you want to add the new shape under or next to, click the arrow on the Insert Shape button on the Organization Chart toolbar, and then click one or more of the following:

Coworker— to place the shape next to the selected shape and connect it to the same superior shape.
Subordinate— to place the new shape below and connect it to the selected shape.
Assistant— to place the new shape below the selected shape with an elbow connector.

If you want to add a preset design scheme, click AutoFormat on the Organization Chart toolbar, and select a style from the Organization Chart Style Gallery.

Click outside the drawing when you are finished.

Draw a line or connector

If you want to use a line to connect shapes and keep them connected, you may want to draw a connector instead of a normal line. A connector looks like a line, but it stays connected to the shapes you attach it to.

Do one of the following:

Draw a line
On the Drawing toolbar, click AutoShapes, point to Lines, and then click the line style you want.

Drag to draw the line.
Do one or both of the following:
To constrain the line to draw at 15-degree angles from its starting point, hold down SHIFT as you drag.

To lengthen the line in opposite directions from the first end point, hold down CTRL as you drag.
If you just want to draw a straight line, click Line on the Drawing toolbar, and then drag to draw the line.

Draw a connector

On the Drawing toolbar, click AutoShapes, point to Connectors, and then click the connector line you want.

Point to where you want to attach the connector.
Connection sites appear as blue circles as you pass the pointer over a shape.
Click the first connection site you want, point to the other object, and then click the second connection site.

Locked or attached connectors appear as red circles. Unlocked connectors appear as green circles.

System Integrator Reduces Cost

2010-02-02T04:54:00.000-08:00

Freedom Automation, an Ohio based systems integrator, recently worked with a packaging OEM customer who wanted to significantly reduce changeover time and run multiple product design. Also important to the projects end results were remote startup and diagnostics, field support, and greater and greater throughput and adjustability. The integrator used the Kinetix Accelerator Toolkit CD, which provided files, program codes, and manuals for implementing a control system. From there, the toolkit provided recommendations for hardware selection, system layout, and even wiring schematics, helping freedom to complete the entire design phase in a matter of hours.

After implementing the solution, Freedom Automation experienced 60 percent to 70 percent in engineering and programming time,. Freedom Automation also experienced a 54 percent cost reduction by using the toolkit.

Though the partnership with Rockwell Automation, able to better serve customer. The initial investment in Rockwell Automation provides a platform for exceptional customer service, not only to the company, but also to the OEM customers and their end users. The important of business impact is: Faster Design means Faster time to Market!

Production Process Technology

2010-01-22T04:39:00.000-08:00

The production of a work piece involve transforming a bank of raw piece from its original state to a finished state by changing its shape or the properties of the material in a series of steps. When no further changes have to be made. It is known as a finished piece or finished part.

The classification of production processes starts from the concept of coherence of the material particles or coherence of the structural elements.

Primary forming consists of making a solid body out of formless material. Included in this category as casting of metals, ceramics and plastic, pressing metal powders and subsequently sintering them, pressing synthetic resins, the production of work pieces by electrolytic deposition.

Reshaping consist of changing the shape of a solid body without adding or removing material (plastic transforming). This category includes remodeling by pressure (extrusion, molding, forging, rolling), by tension and compression (deep drawing wire drawing) by tensile reformation (stretch forming) and by bending.

Changing the properties of the material by reorienting the material particles. This include process in which the internal structure of the material is changed, e.g. tempering, hardening, solid rolling and magnetization.

Cutting is means of reshaping a solid body by overcoming is coherence. Distinctions are made between: dividing, e.g. cutting off, incising, tearing; chip removal (machining), e.g. turning, drilling, grinding, filing, sawing, wearing off material by heal (e.g. torch cutting); separation of previously joined work pieces, e.g. unscrewing, squeezing out: Cleaning of work pieces by brushing, sand blasting, washing, picking.

The group also includes the elimination of material particles, e.g. decarburizing steel. Joining consists of bringing together work piece by combining (insertion and suspension, by adjusting and fitting (wedging, screwing, shrinking) by primary shaping (remolding), deforming, (folding together, wrapping, riveting) by material bonding (welding, soldering, use of adhesives).

Adding material particles, e.g. nitrogen, changes the properties of basic material. Coating consists of spreading a coat of formless material that adhered to the surface of the work piece (painting), vapor depositing, and deposit welding, galvanizing, thermal spraying.

Algorithm Help You

2009-12-01T01:03:00.000-08:00

Wha is the use of algorithm? People use algorithm to explain something to others in order to make other people easy to understand their planning or process running system. Simple map to show the way to certain place also a kind of algorithm form. So algorithm can be called as the clue or flow or the step to reach something or goal.

Process algorithm or process diagram is the order step to reach something, or to get something, like in Industry. The step to produce a certain product need many step to reach the real product. We can't get that product without use the available step, or can't get product faster without use the available step like on the process diagram. In reality the process diagram or process algorithm is not always true, that flow process just a clue and show the current fastest process or current available process or current effective process. The function of algorithm is to show that the available process as their experience, if there are new process algorithm discovery that better than the old one, the process algorithm can be changed.

So on the final step of process diagram then completed with the line back to the beginning to review the available process. If the available process is not good then people can improve with the new one. The changes to make some improvement on the production process always do in order to get highest quality product in order can compete on the market. In all production process is need this back-line-step to improve their product, to improve their service or to improve their system and management. The process on electroplating or the process on anodizing is need this kind of process algorithm to improve the service and product quality.

Canada Process Control Conference

2009-09-16T19:40:00.000-07:00

This process control conference result is conducted in Canada, and called as Canada Process Control Conference. The overall goal of the CPC conference series is to evaluate current progress in the process control field and to identify new intellectual challenges that may have a fundamental impact on future industrial practice. Specific goals of CPC 7 include:

Assess the current state of process control theory and practice.
Present tutorial overviews for non-specialists in relevant areas of systems and control theory, particularly emerging and new areas.
Provide a forum for in-depth discussions between university researchers, industrial practitioners and commercial control technology vendors.
Expose practitioners and vendors to significant new tools emerging from the research community to stimulate wider implementation.
Present promising research directions for the next decade.
Evaluate needs and challenges in the process industries for the next decade.
Evaluate opportunities for applications in non-traditional industries.
Evaluate the current status of process control education at the undergraduate and graduate levels.

CPC 7 is an international conference attracting participants from North and South America, Europe and the Pacific Rim. Based on previous CPC meetings, approximately 50% of the attendees will be from industry and government with the remaining attendees from academia.

Function of Algorithma

2009-08-26T21:41:00.000-07:00

Function of algoritma in drawing of planning something will easy to present to others about what will they planning of something and on this planning people will see the flow of working. On the algorithma chart can be seen that their planing is in wright way or wrong way, and people will can fast correcting the work flow.

The example of planing algorithma as follows:

I will plan to seeding a tomato on the field and what are the step I need, if there are a wrong step will easey to see that the flow is wrong.

Seeding Field Preparation ------> Seeding ------> Planting Field Preparation ------>

Planting ------> fertilizing ------> Plant Treatment ------> Harvesting

Every step of that simple algorithma will describe in more detail if need explanation. If experience people can see that on that diagram there is wrong cycle but for general people just see that the diagram just right. Why are wrong often happen because planting of certain plant may have different cycle, so just experienced people will see that the cycle are wrong.

So that is the function of using flow diagram on presenting some oppinion to other people that hope will have any correction from experienced people, just by one seing sight.

Lets Hear Indonesian Song

2009-07-07T21:25:00.000-07:00

Don't think seriously on, you need getting relax, may just for a moment because this very important for your brain. Hear of slow music will don't disturb you while you work but you can use your right and left brain at the same time. This do by us with no feel but the effect to our brain can better.

Our brain work just as what we do or command something to the nerve network on our brain, nerve then do what the task should do. Our brain work without our realize, brain always create new network on our memory system.

So this is the music of Bunga Citra Lestari from Indonesia, pop music. Here is the video music:

Copy From Music Elements

Multidiscipline Control

2009-04-20T21:29:00.001-07:00

There are essentially three levels of control systems available today: specialty, hybrid and integrated.

Specialty control system performs a single control discipline using development platforms, languages and communications that are specific, and often proprietary, to the discipline. Example include distributed control systems (DCSs), programmable logic controllers (PLCs) and motion controllers. While these systems control specific application types very well, it is generally more expensive overall for you to deploy them throughout your plant. With only about 20% of your total cost of ownership tied up in equipment cost, these specialty controllers are ultimately more difficult and expensive to develop, integrate and maintain.

Hybrid Control Systems can control more than one control discipline by employing multiple control engineers; multiple communication protocols at different system levels; and multiple services oriented architecture (SOAs) in the information space. These systems offer improvements in integration and information availability through the continued use of multiple development environments, control engines and protocols. This still mean that development and maintenance is not optimized, and integration between hybrid elements is still required.

Integrated control systems provide multidiscipline control across user’s internal supply chain, using a single communication protocol and a single SOA for information integration. Integrated systems optimize the plant’s internal supply chain between manufacturing areas to help reduce development, integration, maintenance and operational costs. These integrated systems improve information capabilities and convergence with the user’s IT system to help improve decision-making and use of production assets.

Open Loop Versus Closed Loop

2009-04-09T10:26:00.000-07:00

It is common in industry to manipulate coolant in a jacketed reactor in order to control conditions in the reactor itself. A simplified schematic diagram of such a reactor control system. Assume that the reactor temperature is adjusted by a controller that increases the coolant flow in proportion to the difference between the desired reactor temperature and the temperature that is measured. The proportionality constant is Kc. If a small change in the temperature of the inlet stream occurs, then depending on the value of Kc, one might observe the reactor temperature responses shown in Figure.

The top plot shows the case for no control (Kc = 0), which is called the open loop, or the normal dynamic response of the process by itself. As Kc increases, several effects can be noted. First, the reactor temperature responds faster and faster. Second, for the initial increases in Kc, the maximum deviation in the reactor temperature becomes smaller. Both of these effects are desirable so that disturbances from normal operation have as small an effect as possible on the process under study. As the gain is increased further, eventually a point is reached where the reactor temperature oscillates indefinitely, which is undesirable. This point is called the stability limit, where Kc = Ku, the ultimate controller gain.

Increasing Kc further causes the magnitude of the oscillations to increase, with the result that the control valve will cycle between full open and closed. The responses shown in Figure are typical of the vast majority of regulatory loops encountered in the process industries. On the figure shows that there is an optimal choice for Kc, somewhere between 0 (no control) and Ku (stability limit). If one has a dynamic model of a process, then this model can be used to calculate controller settings.

In Figure, no time scale is given, but rather the figure shows relative responses. A well-designed controller might be able to speed up the response of a process by a factor of roughly two to four. Exactly how fast the control system responds is determined by the dynamics of the process itself.

Logic Control Engine

2009-03-23T04:56:00.000-07:00

At the heart of integrated Architecture lies the logic control engine, providing the power for manufacture and machine builders to increase productivity while reducing total cost of ownership.

The logic control engine resides in a variety of hardware and software options, from the powerful control logic, Programmable Automation Controller (PAC), to the smaller compactlogic “PAC, and even PC-based SoftLogic” controller. Logic provide the basic for fully integrated solution throughout your plant for discrete, motion process, batch, safety and drive applications. The use of a single development environment, Rockwell Software” RSLogic” 5000 programming software, provide you with the appropriate language options for your application, including traditional ladder logic for discrete, function block programming for process, an 588 batch phase manager and even sequential function chart or structured text if you prefer, all in the same controller.

The logic control engine equips you with the ability to reuse engineering design, and shares the untethered tag based system database with other Rockwell Automation integrated Architecture enabling technology to reduce your development and commissioning time.

Integrity of Process Control Systgems

2009-02-23T01:26:00.001-08:00

Ensuring the integrity of process controls involves both hardware issues, software issues, and human issues. Of these, the hardware issues are usually the easiest to assess and the software issues the most difficult.

The hardware issues are addressed by providing various degrees of redundancy, by providing multiple sources of power and/or an uninterruptible power supply, and the like. The manufacturers of process controls provide a variety of configuration options. Where the process is inherently safe and infrequent shutdowns can be tolerated, nonredundant

configurations are acceptable. For more demanding situations, an appropriate requirement might be that no single component failure can render the process-control system inoperable. For the very critical situations, triple-redundant controls with voting logic might be appropriate. The difficulty is assessing what is required for a given process.

Another difficulty is assessing the potential for human errors. If redundancy is accompanied with increased complexity, the resulting increased potential for human errors must be taken into consideration.

Redundant systems require maintenance procedures that can correct problems in one part of the system while the remainder of the system is in full operation. When conducting maintenance in such situations, the consequences of human errors can be rather unpleasant.

The use of programmable systems for process control present some possibilities for failures that do not exist in hard-wired electromechanical implementations. Probably the one of most concern is latent defects or “bugs” in the software, either the software provided by the supplier or the software developed by the user. The source of this problem is very simple. There is no methodology available that can be applied to obtain absolute assurance that a given set of software is completely free of defects. Increased confidence in a set of software is achieved via extensive testing, but no amount of testing results in absolute assurance that there are no defects. This is especially true of real-time systems, where the software can easily be exposed to a sequence of events that was not anticipated. Just because the software performs correctly for each event individually does not mean that it will perform correctly when two (or more) events occur at nearly the same time. This is further complicated by the fact that the defect may not be in the programming; it may be in how the software was designed to respond to the events.

The testing of any collection of software is made more difficult as the complexity of the software increases. Software for process control has progressively become more complex, mainly because the requirements have progressively become more demanding.

To remain competitive in the world market, processes must be operated at higher production rates, within narrower operating ranges, closer to equipment limits, and so on. Demanding applications require sophisticated control strategies, which translate into more complex software. Even with the best efforts of both supplier and user, complex software systems are unlikely to be completely free of defects.

The Benefit of Advance Control

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The economics of most processes are determined by the steady-state operating conditions. Excursions from these steady-state conditions generally average out and have an insignificant effect on the economics of the process, except when the excursions lead to off-specification products. In order to enhance the economic performance of a process, the steady-state operating conditions must be altered in a manner that leads to more efficient process operation.

The following hierarchy is used for process control:

Level 0: Measurement devices and actuators
Level 1: Regulatory control
Level 2: Supervisory control
Level 3: Production control
Level 4: Information technology

Levels 2, 3, and 4 clearly affect the process economics, as all three levels are directed to optimizing the process in some manner. However, level 0 (measurement devices and actuators) and level 1 (regulatory control) would appear to have no effect on process economics.

Their direct effect is indeed minimal, but indirectly, they have a major effect. Basically, these levels provide the foundation for all higher levels. A process cannot be optimized until it can be operated consistently at the prescribed targets. Thus, a high degree of regulatory control must be the first goal of any automation effort. In turn, the measurements and actuators provide the process interface for regulatory control.

For most processes, the optimum operating point is determined by a constraint. The constraint might be a product specification (a product stream can contain no more than 2 percent ethane); violation of this constraint causes off-specification product. The constraint might be an equipment limit (vessel pressure rating is 300 psig); violation of this constraint causes the equipment protection mechanism (pressure relief device) to activate. As the penalties are serious, violation of such constraints must be very infrequent.

If the regulatory control system were perfect, the target could be set exactly equal to the constraint (that is, the target for the pressure controller could be set at the vessel relief pressure). However, no regulatory control system is perfect. Therefore, the value specified for the target must be on the safe side of the constraint, thus giving the control system some “elbow room.” How much depends on the following:

The performance of the control system (i.e., how effectively it responds to disturbances). The faster the control system reacts to a disturbance, the closer the process can be operated to the constraint.
The magnitude of the disturbances to which the control system must respond. If the magnitude of the major disturbances can be reduced, the process can be operated closer to the constraint.

One measure of the performance of a control system is the variance of the controlled variable from the target. Both improving the control system and reducing the disturbances will lead to a lower variance in the controlled variable.

In a few applications, improving the control system leads to a reduction in off-specification product and thus improved process economics. However, in most situations, the process is operated sufficiently far from the constraint that very little, if any, off-specification product results from control system deficiencies. Management often places considerable emphasis on avoiding off-spec production, so consequently the target is actually set far more conservatively than it should be.

In most applications, simply improving the control system does not directly lead to improved process economics. Instead, the control system improvement must be accompanied by shifting the target closer to the constraint. There is always a cost of operating a process in a conservative manner. The cost may be a lower production rate, a lower process efficiency, a product giveaway, or otherwise. When management places extreme emphasis on avoiding off-spec production, the natural reaction is to operate very conservatively, thus incurring other costs.

The immediate objective of an advanced control effort is to reduce the variance in an important controlled variable. However, this effort must be coupled with a commitment to adjust the target for this controlled variable so that the process is operated closer to the constraint. In large throughput (commodity) processes, very small shifts in operating targets can lead to large economic returns.

Cause and Effect Diagram

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Graphically illustrates the relationship between a given outcome and all the factor that influence this outcome. Sometimes called an Ishikawa or “fishbone diagram.” It helps show the relationship of the parts (and sub-parts) to the whole by:

Determining the factor that cause a positive or negative outcome (or effect)
Focusing on a specific issue without resorting to complaints and irrelevant discussion
Determining the root causes of a given effect
Identifying areas where there is a lack of data

How to use:

Specific the effect to be analyzed. The effect can be positive (objectives) or negative (problems). Place it in a box on the right side of the diagram.

--------------------> Problem

List the major categories of the factors that influence the effect being studied. The “4Ms” (methods, manpower, people, plant are commonly used as a starting point.

ROLE OF AUTOMATION IN PLANT SAFETY

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As microprocessor-based controls displaced hardwired electronic and pneumatic controls, the impact on plant safety has definitely been positive. When automated procedures replace manual procedures for routine operations, the probability of human errors leading to hazardous situations is lowered. The enhanced capability for presenting
information to the process operators in a timely manner and in the most meaningful form increases the operator’s awareness of the current conditions in the process. Process operators are expected to exercise due diligence in the supervision of the process, and timely recognition of an abnormal situation reduces the likelihood that the situation will progress to the hazardous state. Figure 8-88 depicts the layers of safety protection in a typical chemical plant.

Although microprocessor-based process controls enhance plant safety, their primary objective is efficient process operation. Manual operations are automated to reduce variability, to minimize the time required, to increase productivity, and so on. Remaining competitive in the world market demands that the plant be operated in the best manner possible, and microprocessor-based process controls provide numerous functions that make this possible. Safety is never compromised in the effort to increase competitiveness, but enhanced safety is a by-product of the process-control function and is not a primary objective.

By attempting to maintain process conditions at or near their design values, the process controls also attempt to prevent abnormal conditions from developing within the process. Although process controls can be viewed as a protective layer, this is really a by-product and not the primary function. Where the objective of a function is specifically to reduce risk, the implementation is normally not within the process controls. Instead, the implementation is within a separate system specifically provided to reduce risk. This system is generally referred to as the safety interlock system.

As safety begins with the process design, an inherently safe process is the objective of modern plant designs. When this cannot be achieved, process hazards of varying severity will exist. Where these hazards put plant workers and/or the general public at risk, some form of protective system is required. Process safety management addresses the various issues, ranging from assessment of the process hazard to assuring the integrity of the protective equipment installed to cope with the hazard. When the protective system is an automatic action, it is incorporated into the safety interlock system, not within the process controls.

PROCESS CONTROL AND PLANT SAFETY

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Accidents in chemical plants make headline news, especially when there is loss of life or the general public is affected in even the slightest way. This increases the public’s concern and may lead to government action. The terms hazard and risk are defined as follows:

Hazard. A potential source of harm to people, property, or the environment
Risk. Possibility of injury, loss, or an environmental accident created by a hazard Safety is the freedom from hazards and thus the absence of any associated risks. Unfortunately, absolute safety cannot be realized.

The design and implementation of safety systems must be undertaken
with a view of two issues:

Regulatory. The safety system must be consistent with all applicable codes and standards as well as “generally accepted good engineering practices.”
Technical. Just meeting all applicable regulations and “following the crowd” does not relieve a company of its responsibilities. The safety system must work.

The regulatory environment will continue to change. As of this writing, the key regulatory instrument is OSHA 29 CFR 1910.119 that pertains to process safety management within plants in which certain chemicals are present.

In addition to government regulation, industry groups and professional societies are producing documents ranging from standards to guidelines. Instrument Society of America Standard S84.01, “Application of Safety Instrumented Systems for the Process Industries,” is in draft form at the date of this writing. The Guidelines for Safe Automation
of Chemical Processes from the American Institute of Chemical Engineers’ Center for Chemical Process Safety (1993) provides a comprehensive coverage of the various aspects of safety, and, although short on specifics, it is very useful to operating companies developing their own specific safety practices (that is, it does not tell you what to do, but it helps you decide what is proper for your plant).

The ultimate responsibility for safety rests with the operating company; OSHA 1910.119 is clear on this. Each company is expected to develop (and enforce) its own practices in the design, installation, testing, and maintenance of safety systems. Fortunately, some companies make these documents public. Monsanto’s Safety System Design Practices was published in its entirety in the proceedings of the International Symposium and Workshop on Safe Chemical Process Automation, Houston, Texas, September 27–29, 1994 (available from the American Institute of Chemical Engineers’ Center for Chemical
Process Safety).

THE GENERAL CONTROL SYSTEM

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Variations in load will drive the controlled variable away from set point, requiring a corresponding change in the manipulated variable to bring it back. The manipulated variable must also change to move the controlled variable from one set point to another.

An open-loop system positions the manipulated variable either manually or on a programmed basis, without using any process measurements. This operation is acceptable for well-defined processes without disturbances. An automanual transfer switch is provided to allow manual adjustment of the manipulated variable in case the process or the control system is not performing satisfactorily.

A closed-loop system uses the measurement of one or more process variables to move the manipulated variable to achieve control. Closedloop systems may include feedforward, feedback, or both. Feedback Control In a feedback control loop, the controlled variable is compared to the set point R, with the difference, deviation, or error e acted upon by the controller to move m in such a way as to minimize the error. This action is specifically negative feedback, in that an increase in deviation moves m so as to decrease the deviation.

(Positive feedback would cause the deviation to expand rather than diminish and therefore does not regulate.) The action of the controller is selectable to allow use on process gains of both signs. The controller has tuning parameters related to proportional, integral, derivative, lag, deadtime, and sampling functions. A negative feedback loop will oscillate if the controller gain is too high, but if it is too low, control will be ineffective.

The controller parameters must be properly related to the process parameters to ensure closed-loop stability while still providing effective control. This is accomplished first by the proper selection of control modes to satisfy the requirements of the process, and second by the appropriate tuning of those modes.

Feedforward Control A feedforward system uses measurements of disturbance variables to position the manipulated variable in such a way as to minimize any resulting deviation. The disturbance variables could be either measured loads or the set point, the former being more common. The feedforward gain must be set precisely to offset the deviation of the controlled variable from the set point.

Feedforward control is usually combined with feedback control to eliminate any offset resulting from inaccurate measurements and calculations and unmeasured load components. The feedback controller can either bias or multiply the feedforward calculation.

Computer Control Computers have been used to replace analog PID controllers, either by setting set points of lower level controllers in supervisory control, or by driving valves directly in direct digital control. Single-station digital controllers perform PID control

in one or two loops, including computing functions such as mathematical operations, characterization, lags, and deadtime, with digital logic and alarms. Distributed control systems provide all these functions, with the digital processor shared among many control loops; separate processors may be used for displays, communications, file servers, and the like. A host computer may be added to perform highlevel operations such as scheduling, optimization, and multivariable control. More details on computer control are provided later in this section.

Process Diagram

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The example of process diagram are as on the example drawing below, this diagram is explain on the pneumatic network process. On this diagram using a specific peneumatic symbol that function for specific process such as valve 5/2 or valve 4/2 that explain the air in and air out from the valve.

Algorithm

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An algorithm is a procedure for solving a usually complicated problem by carrying out a precisely determined sequence of simpler, unabigous steps. Such procedures were originally used in mathematical calculations (the name is a variant of algorithm which originally meant the Arabic numerals and then "arithmetic") but are now widely used in computer program and in programmed learning. Flowcharts are frequently used to facilitate understanding of the sequence of steps.

Algoritma is usually used for describing the process of management flow that should be done in orderly but sometime should be done in the same period time or in the same time, according to the process flow order.

Process Control

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Process control is a general term applied to describe the many methods of regulating the values of variables involved in industrial operations, temperature, and flow rate of raw materials. In fact any quantity that requires regulation in an industrial process can be treated as a variable for process control.

An integral part of the industrial resolution and the ensuing manufacturing innovations was the necessity to many different production parameters. For example, to manufacture plastic it may be necessary to maintain the temperature of a reason vessel at a constant value. If the process were not controlled, the temperature of the vessel might vary radically and create a poor-quality product or even a dangerous situation. Procedures have been developed to provide such regulation. Regulation was accomplished manually at first, through measurement, evaluation, and adjustment of the variable. Later, automatic systems were developed that could measure, evaluate, and adjust without direct human interaction. Automatic regulation of this type makes use of the feedback of the value of a variable in order to effect necessary adjustments of the process involving that variable.

The complete assembly of the three elements, measurement, evaluation, and adjustment, constitutes what is called a process control loop, where the word loop convey the idea of feedback of adjustments to the process following measurements in the process. Most industrial operations involve many variables to be regulated and thus many such process control loops. Sometimes the loop variables interact with each other so that adjustments for one variable affect a second variable, and so on. The overall process-control system is the assemblage of all these loops.

Since the late 1970s, microprocessor-based process control systems have come into wide use. Depending on the user’s need, such systems use an array of microprocessors to control from one to hundreds of variables. Further, these microprocessors are “cross-coupled,” or connected, with each other in such a way that complex adjustments can be made across a series of variables based on information traded between microprocessors.

Process Algoritma

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Process algoritma may similar with process diagram. Process algoritma will describe the process description using algoritma. Algoritma make us more simple on watching the overall process on certain plant or on other step process. Algoritma also can draw to the reader the step flow that happen on the system.

For more detail about this algoritma may can view on the drawing of every process that available on this blog.