PARAMETER DESIGN OF AN
ELECTRO PNEUMATIC SYSTEM
USING RESPONSE SURFACE
METHODOLOGY
Rajakannu Amuthakkannan
Associate Professor, Caledonian College of Engineering,
Muscat, Sultanate of Oman r.amuthakannan@gmail.com
Abstract
In the present scenario, more number of software based mechanical systems are coming with advanced technologies like embedded system control or computer system control for various industrial applications. Mechatronics is a popular technology in the evolutionary process of modern engineering automation system design. The ineffective parameter design in software based mechatronics system may produce the severe consequences in the application field, even there is a chance of accidents. So, careful process parameter design is an essential issue in software based mechatronics systems. The response surface methodology has widely used in industry for the purpose of finding factors that are most important in achieving useful goals in any processes. This research outlines the optimization of parameters in a software based electro pneumatic system for the response of time taken to complete the sequence of operations by applying response surface methodology. In this work, the parameters from both hardware and software products are taken to analyze the software based mechatronics system.
Keywords— Software based Mechatronics system, Response surface methodology, Optimization 1. Introduction
In high Precision manufacturing, software based systems are widely used to automate various processes. The advances in microchip and computer technology have bridged the gap between traditional electronic control and process control engineering. The increasing demand on quality and productivity of products and services change the industrial dynamics on several fronts including economics, research, technical knowledge, software, latest electronics and communication technologies and so on. To match these demands of increased quality at lower cost, more and more industries are moving towards software based system. Software based automation systems are generally defined as the process of having systems to follow predetermined sequences of operations with no human labour, using specialized equipment and devices that perform control of the involved processes in the system with the help of software. In the present scenario, more number of software based mechanical systems are coming with advanced technologies like embedded system control or computer system control for various industrial applications. A modern electro mechanical system consists of sophisticated software and hardware components to achieve high precision manufacturing processes. These types of systems are called software based mechatronics systems. Due to various applications of mechatronics concepts in modern engineering fields, high reliability, high quality software, defect free network system and accurate design of process parameters are some of the conditions to construct a best and quality oriented system.
2. Software Based Mechatronics System
and nano electro mechanical systems (MEMS and NEMS) etc. Figure 1 shows the elements and information flows of an automation system.
Figure 1 Elements of mechatronics system
The introduction of software and digital technology in mechatronics systems which are applied in safety critical systems has many advantages both concerning flexibility and reliability. In such type of systems, software and hardware system design has a continuously increasing impact on system reliability [4]. So, quality of design, quality conformance and quality improvement are essential issues in the construction of new generation mechatronics system.
3. Background of the Research
The software based system contains different hardware and software modules for accessing the real time data and producing the required outputs. Integrating the hardware modules with software modules in the real time environment is not a simple one, it may be affected by various factors such as voltage, software logics and design factors, environmental factors etc. If the number of modules is increased in the real time system, the system complexity will increase. Due to the system complexity, the real time system provides the invalid outputs in the application environment. So, the system’s quality and reliability should be estimated and improved in the development stages of software based systems [1]. Successful mechatronics design can lead to products that are extremely attractive to the consumer in quality cost-effectiveness. So, it is important to produce novel, high technology design and development of system with highest quality. The real challenge in this research work is to connect various fields in a clear and concise manner to obtain a well-designed software based mechatronics systems. In software based systems, it is not only the important of improving software design, it is also important of optimal design of process parameters to improve the quality of the system. It is essential that software based systems provide an accurate and robust performance over a wide range of input conditions [2]. The Response surface methodology method of experimental design has been widely used in industry for the purpose of finding factors that are most important in achieving useful goals in a manufacturing process. This paper outlines the response surface methodology optimization methodology for software based mechatronics system.
4. Response Surface Methodology
The Response Surface Methodology (RSM) is important in designing and analyzing products and processes. It is optimization study for existing studies and products. The most common applications of RSM are in Industrial, Biological and Clinical Science, Social Science, Food Science, Physical and Engineering Sciences. Response surface methodology will give a solution in either 2-Dimensional or 3 Dimensional to get a perfect solution for the parameter setting to get optimal solution for a response [6].
5. Case Study
5.1 Software based automation system Example
Lab VIEW Software for automation system is easy compared with other software in the point of data acquisition, signal conditioning, interfacing and analysis. A cascading Electro pneumatic system is considered for analysis to find the delay time taken to complete the sequence of X+Y+Y-X- (X+ is the Extension of piston in the first cylinder Y+ is the Extension of piston in the second cylinder Y- is the return stroke of piston in the second cylinder X- is the return stroke of piston in the first cylinder) . An electrically controlled fluid power system can be either of the open loop or closed loop type, depending on the application required. This type is characterized by the fact that the fluid power system interacts with a variety of electrical components for control purposes. Here the system contains the devices of solenoid operated direction control valve (DCV), flow control valve (FCV), magnetic cylinder, reed switch, pressure sensor and solenoid operated air control valve. The figure 2 shows the closed loop electro pneumatic circuit, which consists of software system to control the actuation of the cylinder. Actuation of the directional control valve is done by the signal, which is given by the system software. In this system, solenoid operated air control valve is mounted in the outlet of the compressor. This is also controlled by system software. After the signal is delivered from the software system to open the air control valve, the air is filtered, controlled and lubricated in the FRL unit (Filter Regulator Lubricator unit). Then it goes through directional control valve to flow control valve where the flow direction and adjustment is performed and controls the flow of air. Pressure sensor is mounted in between the FCV and cylinder to monitor the air pressure. Initially the magnetic cylinder-X is extended in forward direction (X+). The reed switches are mounted on the magnetic cylinder, which are used to identify the piston’s extreme positions. In the forward direction reed switch-2 will be energized and gives the signal to software control unit. After receiving the signal from reed switch-2, the control unit gives the signal to solenoid Y1 of DCV-2 to get forward direction in magnetic cylinder- Y (Y+). In the extreme forward position of magnetic cylinder-Y’s piston, reed switch-4 will be energized and the signal is transmitted from reed switch- 4 to control system module. Now the control signal should be delivered to get the retraction in magnetic cylinder Y. If it is delivered a control signal to DCV-2 of Y2, there is a chance of fighting signal inside the DCV-2. This is called as cascading in the pneumatic circuits. It should not happen in the circuits. So it is needed to arrest the air flow which is passing through DCV-2 for forward direction. So, the pressure line-I is deactivated and pressure line-II is activated by giving a control signal from software system to cascading valve (4/2 directional control valve). After doing this, the flow of air for forward direction is arrested. Now the air will flow from pressure line-II to magnetic cylinder-Y to get retraction (Y-). Now reed switch-3 is energized when the extreme retraction position is reached and the signal is provided to the control system. After that, the control signal is transmitted from the software system to X2 of DCV-I to achieve the retraction in magnetic cylinder X. (X-). After the cylinder has fully retracted the reed switch-1 will be energized and it gives the signal to software system. The software gives output to cascading valve to change the direction of spool to control the pressure line I and II according to the application. The pressure sensors are mounted in between the FCV and cylinders which are used to monitor the air flow with the required pressure. This process is performed cyclically [5]. The figure 3 shows the experimental setup.
Figure 2 Circuit of pneumatic system
Fig 3 Experimental setup
The time response equation for the parameter interaction is generated as follows Time =+5.15+0.21 * A-0.093 * B+0.13 *
C+0.22 * D+0.044 * A * B+ 0.25 * A * C -0.091 * A * D+ 0.40 * B * C-0.15 * B * D-
0.19 * C * D-0.097 * A2-0.072 * B2 -0.14 * C2-0.14 * D2
ANOVA Table for the given input is shown in table 3
Table 3 ANOVA Table
Fig. 4 Regression plot
5.2 Confirmation Experiment
The confirmation experiment is highly recommended to verify the experimental conclusions from the previous round of experimentation. The optimum condition is set for the significant factors and levels and several tests are made under constant conditions. If the average of the results of the confirmation experiment is within the limits of confidence interval, then the experimenter believes the significant factors as well as the appropriate levels for obtaining the desired result were properly chosen.
Fig.6 3-D surface plot
So the optimal values are predicted as follows in table 4 for the response value 4.98 milli second
Table 4 optimum parameter from RSM
Symbol
Controllable factors
Optimum value from RSM Technique
A Voltage (V) 240
B Operating pressure of magnetic cylinder
(Psi) 225 C Number of requirements per module 2
D Cyclomatic Complexity 11 6. Conclusions
References
[1] Amuthakkannan, R., Kannan, S.M., Selladurai, V. and Vijayalakshmi, K. (2008) ‘Software quality measurement and improvement for real time systems using quality tools and techniques – a case study’, Int. J. Industrial and Systems Engineering, (Inderscience Publications), Vol. 3,No. 2, pp.229–255.
[2] Amuthakkannan, R., Kannan, S.M. and Satheeshpandian (2007) ‘Reliability analysis of software based electro pneumatic system using Bayesian network’, Proceedings of the 2nd International Conference on Mechatronics, Malaysia, pp.805–811.
[3] Bolton, W. (2007) ‘Mechatronics-electronics control systems in mechanical and electrical engineering’, Third Edition, Pearson Education Ltd., and Dorling Kindersley Publishing Inc.,New Delhi, India.
[4] Kant, K. (1990) ‘Performance analysis of real time software supporting fault-tolerant operation’, IEEE Transactions on Computers, Vol. 39, No. 7, pp.906–918.
[5] Esposito, A. (1997) ‘Fluid Power with Applications’, 4th edition, Prentice Hall, India
