Process Control Engineering in Western Australia - Case Study Example

Process Control Engineering in Western Australia Student’s Name Institutional Affiliation Process Control Engineering in Western Australia Process control is a widely recognized mechanism of keeping industries competitive within the international market. The procedure is interdisciplinary in nature and integrates the knowledge of computer science and control engineering to industrial process. A system of process control in engineering supervises the manufacturing environment and controls the flow and processes electronically or mechanically. Controls are undertaken at every stage as designed and set by the users of the system (Johnson, 2014). This paper examines different approaches of process control in Western Australia. Cascade Control The cascade control strategy is often applied in process control systems. Its main objective is to eliminate the impacts that arise from disturbances and improve the performance of control systems. In the event that one controller is used to manipulate the set point of another controller, it can be stated that the two controllers are cascade and the procedure is referred to as a cascade control system (Rao, 1993). (i) Process Modelling for control The system involves the use of a secondary (slave) control loop that is inserted to regulate a variable that is the main source of load disturbance for a main (master) loop control loop. The controller is determined by the setting position of the summing controller in the minor loop (PAcontrol, 2016).When disturbances occur, they have an impact on the primary procedure that is to be controlled. The cascade control system is able to minimize the impact of disruptions that enter the secondary variable through the primary output. Also, the approach can lower the impact of the secondary process or actuator to attain variations on the performance of the control system. In most cases, the differences emerge from the alterations that arise from the operation because of sustained disturbances or changes (Rao, 1993). In West Australian the Cascade system has been applicable in pharmaceutical industries. A heat exchanger is a typical illustration of cascade control. Image 1.0 Demonstrates how the Cascade Control Works (ii)Sensors and Instrumentations Used The approach uses control loops. Due to complexity such as unacceptable lags and overshoots the use of a single loop is not effective. Consequently, two or more loops are used in the process. Each loop used should produce its own output. The cascade loops are invariably fitted to avert external disturbances from entering the process. For the loops to be successful the slave has to be faster than the master. Various sensors and instruments are integrated in the control loops. This include controllers, sensors, pumps, valves and transmitters (PAcontrol, 2016). iii) Details Of Unit Operations In most scenarios, the use of the cascade system is geared towards enhancing the control of the variables in the outer loops. This majorly occurs in surge vessels that undertake fluid processes and heat transfer processes. As shown in image 2.0 below, in the event that a disturbance arises, the flow will have an impact of the level of fluid in the vessel, however, this will not take place speedily. Consequently, it exposes the downstream unit to distresses from the altered flow (VanDoren, 2014). The second controller takes up the role of manipulating the opening of the valve on the basis of the measurements that exist on the next sensor. The first controller does not dictate how extensive the valve should be open, but rather, it informs the second controller about the amount of heat it requires in terms of a stream flow unit. Another role performed by the second controller is to protect the first controller from a decline in the performance of the valve. Sometimes the valve indicates a decline in performance as it gums up or wears out. The second controller therefore works to ascertain that the first controller is not affected by maintaining the rate of stream flow as required (VanDoren, 2014). Figure 2.0 The operation of the control iii) The laws of conservation of mass and energy The pneumatic positioning system below comprises of a proportional servovalve 5/3 that drives a rodless cylinder with internal diameter of 0.025m and 1m stroke. The internal energy contained in the mass that flows into chamber 1 is CpQm1T where Cp is the temperature of air supply, the pressure specific heat of the air, and the flow rate of the air mass into chamber 1. The rate of doing work by the moving piston is p1 where p1 is chamber 1’s absolute pressure and is the volumetric flow rate. > (dV1/dt). The rate of change of internal energy in the cylinder is d(Cvr1V1T1)/dt where CV is the constant heat of the air that is specific to the volume and r1 is the density of the air. The ratio between the specific values of heat is r = CP/CV, and in the case of an ideal gas, r1 = CV/(RT) (Guenther et al., 2006). The resultant energy balance is as shown below The Discrete Control System The approach involves controlling a series of events as opposed to variation or regulation of individual variables. In West Australia, companies that manufacture paint such as Topdek paints, Paint Industries PTY Ltd and Cameleon Coatings often apply the discrete control system. The process adopted by the company’s entails the regulation of various variables such as mixing liquids into the tanks, mixing temperature and observing the flow rates of the liquids. However, it is essential to acknowledge that a series of procedures have to take place in the entire process. The events are to begin and end at a specified time. In the context of the paint manufacturing, the assortment has to be heated at a specific temperature for a certain period of time. It can later be stirred at a different time. The approach is usually implemented through the use of a programmable logic controllers (PLCs) which is a specialized computer based apparatus. (Johnson, 2014). Discrete controllers are normally situated in two positions or models. The two positions are the on and off section. For instance, a typical illustration of the working of the discrete controller can be demonstrated by a water heater. In the vent that the temperature of the water in the tank drops below the set standard, the burners is put on. On the other hand, when the water attains the set standard, the burner is turned off. This occurs because the burner begins to cool when it is tuned off. The same cycle is then repeated. According to PAcontrol (2016), discrete controllers do not hold a variable within a specific set point, but it maintains the variable within the proximity of the set point in what is referred to as the dead zone. Figure 4.0 highlights the process. Figure 4.0: The Discrete Control System The Continuous Control Approach Controllers are usually classified according to their mode of operation and the response of the controller (Bakshi, 2008). For instance, in the context of room temperature, when a heater is to be controlled, it is supposed to be switched on and off in the event that the temperature exceeds the set point. The operation is then defined as a discontinuous operation mode. However, in the same procedure, the use of the on or off approach is not adequate. There is need to close and open the valve. In such a scenario, the controller is referred to as the continuous mode (Bakshi, 2008) Continues controllers seek to make a comparison of the value of Process Variables (PV) to the Set Point (SP). The key objective of the comparison is to evaluate if an errors has taken place. In the event that there is an error, the controllers corrects its output in correlation to the parameters set by the controllers. The key variables to be examined include; the duration of the application of the correction, the magnitude of the correction and the speed at which the rectification is made (PAcontrol, 2016).The figure below demonstrates the working of the continuous control. Figure 5.0: Continuous Controllers In Western Australia, approach is often used in industries that manufacture plastics and chemicals such as such as Graf Plastics Australia and Polytech plastics. The company’s produce large numbers of products each year. The use of the continuous controllers have been useful in temperature control during the production process. Batch Control The approach is widely used in contemporary industries in the production of merchandise that require high efficiency and consistency (Liu and GAO, 2011). The batch process is commonly referred to a procedure that results to the creation of finite material quantities by exposing them to an ordered set of procedures over a restricted period of time. In most cases, a typical cycle of the use of batch control involves steps such as the change over- phase, cleanup, shutdown, start-up and operation. A batch switch is used to deactivate/ activate controllers that are needed at various stages (Polke, 2008). The procedure is commonly applied in process industries. Some of the key areas that exist in Western Australia include pharmaceutical industries and in juice manufacturing industries. A case in point of the use of the approach is when mixing the elements that are used in the production of juices. Several flavors are used, for instance, apple, lemon and orange flavors. In order for the assortment to be sufficient, it is important for the procedure to be continuous. The batch process, therefore, entails integrating the right proportion of constituents into the batch. Temperature, pressure and the level of flow have to be measured constantly. The key limitation of the procedure is that it has to be restarted frequently. The constant start-up leads to problems in the control procedure. Also, another demerit is that as the recipes continue to change, the equipments of control have to be remarked (PAcontrol, 2016). Fuzzy logistic Control (FLC) The fuzzy logic control (FLC) presents a nonanalytic substitute to the classical analytic control theory. The basis of fuzzy control is an I/O function that maps every low-resolution quantization interval into a very low-low quantization interval. The low-resolution quantization interval is of the input domain whereas the low-low quantization interval is of the output domain. Only seven or nine quantization intervals cover the output and input domains. Consequently, it is easy to express the mapping relationship using the “if-then” formalism. The result is using less design time to achieve a simpler solution. The linear membership functions and the overlapping of the fuzzy domains enable the attainment of a high-resolution I/O function between output variables and crisp input (Petriu, 1972). The figures below show the fuzzy logic control. A fuzzy quantity refers to a normalized fuzzy set containing either a decreasing or an increasing membership function. As a result, there are left and right bounds to the kernel whereas the other side is unbounded. Fuzzification refers to the process of converting a process quantity into a fuzzy quantity. On the other hand, defuzzification refers to the process of converting a fuzzy quantity into a process quantity (Zimic & Mraz, 2006). In essence, defuzzification is the reverse of fuzzification. In Western Australia, firms use the fuzzy controller in the docking of trailer and truck. Processing several fuzzy decisions enables effective truck and trailer docking through three fundamental steps. The first step entails determining the membership degree of the input variable’s crisp value using already defined fuzzy sets through the fuzzification process. The second step entails processing the fuzzy decision through the evaluation of fuzzy rules, a process called implication. The last step entails determining the crisp value of the output variable commonly referred to as the crisp decision, a process called defuzzification. The fuzzy controller plays a pivotal role in truck and trailer reverse packing thereby making the complex non-linear process to appear easy. In the implementation of the system, the controller ensures that the truck and trailer system is in the desired position within the shortest time possible by restricting the motion of the system to reverse driving only. The system uses a predefined threshold for the angle between the truck and trailer (Zimic & Mraz, 2006). Consequently, the actual angle between the truck and trailer should not exceed the threshold during the ride. Conclusion The above discussion has examined process control in engineering. Some of the common approaches of engineering process control that are mainly used in Western Australia include: cascade, batch control, the continuous control approach, the fuzzy control and discrete control system. The paper underscores the fact that process control is significant in many industries in the region. This include juice manufacturing, plastic manufacturing and pharmaceutical industries. The approaches involve the control of the flow of materials, pressure, and temperature. Just like procedures in other industrial environments, manufacturing setups in Australia depend on engineering process control. In conclusion, the paper identified the fact that the processes have unique and distinct functions and procedures. References Bakshi, V. (2008). Control Systems. Technical Publications. Guenther, R., Perondi, E. A., DePieri, E. R., & Valdiero, A. C. (2006). Cascade controlled pneumatic positioning system with LuGre model based friction compensation. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 28(1), 48-57. Liu, T and Gao, F. (2011). Batch Process Control. Industrial Process Identification and Control Design. Advances in Industrial Control pp 433-452 Johnson, C. (2014). Process Control Instrumentation Technology. Pearson. PAcontrol. (2016). Instrumentation and Control. PAControl.com Petriu, E. M. (1972). Fuzzy systems for control applications. Lecture Notes. Rao, R. (1993). Process Control Engineering. CRC Press. VanDoren, V. (2014). Fundamentals of cascade control. Control Engineering. Polke, M. (2008). Process Control Engineering. John Wiley & Sons. Zimic, N & Mraz, M. (2006). Decomposition of a complex fuzzy controller for the truck-and-trailer reverse parking problem. Mathematical and Computer Modelling, 43(5), 632-645. Read More