Process Parameters Optimization: A Design Study for TiO2 Thin Film of Vacuum Sputtering Process

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, VOL. 7, NO. 1, JANUARY 2010 143

Short Papers

Process Parameters Optimization: A Design Study for TiO Thin Film of Vacuum Sputtering Process Wen-Hsien Ho, Jinn-Tsong Tsai, Gong-Ming Hsu, and

Jyh-Horng Chou

Abstract—This paper proposes a procedure for process parameters design by combining both modeling and optimization methods. The proposed procedure integrates the Taguchi method, the artificial neural network (ANN), and the genetic algorithm (GA). First, the Taguchi method is applied to minimize experimental numbers and to collect experimental data representing the quality performances of a system. Next, the ANN is used to build a system model based on the data from the Taguchi experimental method. Then, the GA is employed to search for the optimal process parameters. A process parameters design for a titanium dioxide (TiO ) thin film in the vacuum sputtering process is studied in this paper. The quality objective is to form a smaller water contact angle on the

TiO thin-film surface. The water contact angle is 4 obtained from the

system model of the proposed procedure. The process parameters obtained from the proposed procedure were used to conduct the experiment in the vacuum sputtering process for theTiO thin film. The water contact angle given from the practical experiment is 3.93 . The difference percent is 1.75% between 4 and 3.93 . The result obtained from the system model of the proposed procedure is promising. Hence, we can conclude that the proposed procedure is a very good approach in solving the problem of the process parameters design.

Note to Practitioners—This paper was motivated by the problem of finding optimal process parameters for theTiO thin film but it also ap-plies to other different processes that need to get better process parameters by experiments. Existing approaches have trial-and-error or experimental design methods. The two methods are time- and cost-consuming, and could not guarantee to find the good process parameters. This paper suggests a procedure by combining both modeling and optimization methods to solve this problem. We employ the Taguchi method, the ANN, and the GA to search for the optimal process parameters for aTiO thin film in the vacuum sputtering process. The result is quite promising. In future research, we will improve the adopted methods and apply the approach to other problems for optimal process parameters design. Please feel free to contact us, if you have any questions about this approach. We will do our best to help you.

Index Terms—Genetic algorithm (GA), neural network, Taguchi method, thin film, vacuum sputtering process.

I. INTRODUCTION

Environmental pollution and destruction on the globe have drawn attention to develop totally new, safe, and clean chemical technologies and processes. These topics have been to be the most important chal-lenge in the industries of the 21st century. Thus, photocatalysis

tech-Manuscript received June 16, 2008; revised October 13, 2008. First pub-lished July 24, 2009; current version pubpub-lished January 08, 2010. This paper was recommended for publication by Associate Editor M. Zhang and Editor V. Kumar upon evaluation of the reviewers’ comments. This work was sup-ported in part by the National Science Council, Taiwan, under Grant NSC96-2221-E153-002-MY2 and Grant NSC96-2628-E327-004-MY3.

J.-T. Tsai is with the Department of Computer Science, National Pingtung University of Education, Pingtung 900, Taiwan.

W.-H. Ho is with the Department of Medical Information Management, Kaohsiung Medical University, Kaohsiung 807, Taiwan.

G.-M. Hsu is with the Metal Industries Research and Development Centre, Kaohsiung 811, Taiwan.

J.-H. Chou is with the Institute of System Information and Control, National Kaohsiung First University of Science and Technology, Kaohsiung 824, Taiwan (e-mail: choujh@ccms.nkfust.edu.tw).

Digital Object Identifier 10.1109/TASE.2009.2023673

nologies are becoming more and more attractive to the industries today. In the studies of Fujishima et al. [3], [4],TiO₂shows the advantages of strong oxidation power, stable chemical and heat resistance proper-ties, low cost, corrosion resistance, and high decomposition efficiency as well as the super hydrophilicity. In the manufacturing process of the TiO2thin film, the physical vapor deposition (PVD) of vacuum sput-tering process has the advantages of high adhesion and compactness. Currently, the vacuum sputtering process producing theTiO2thin film commonly adopts trial-and-error or experimental design methods. That is, one is to presume the initial experimental parameters, then modify and verify the experimental data to obtain feasible process parameters. The other is to collect and adjust the experimental parameters obtained from the past similar experiments to find better process parameters [11], [13], [16]. All of those methods are time- and cost-consuming, and could not guarantee to find the good process parameters. There-fore, it is very important to develop an effective procedure to search for optimal process parameters.

The Taguchi method [14], [17], [20] uses many ideas from the sta-tistical experimental design for evaluating and implementing improve-ments in products, processes and equipment. The Taguchi method is used to study a large number of design variables with a small number of experiments. The better level combinations of design variables are decided by the orthogonal arrays (OAs) and signal-to-noise ratios (). The artificial neural network (ANN) is a powerful data modeling tool that is able to capture and represent complex input/output relationships [5], [7], [8]. A multilayer ANN can approximate any nonlinear contin-uous function to an arbitrary accuracy [2], [9], [19]. Owing to its par-ticular structure, a neural network is very good in learning using some learning algorithms such as the genetic algorithm (GA) [1], [6], [18], [19] and the backpropagation [12].

In this paper, we integrate both modeling and optimization methods to propose the parameters design procedure. The proposed procedure combines the Taguchi method, the ANN, and the GA. The detailed pro-cedure for designing the process parameters is described as follows. First, define the experimental problems and parameters, and use the Taguchi method with a small experimental numbers to do experiments and collect data representing the quality performances of a system. Next, establish and verify the system model by using the ANN based on the data from the Taguchi experimental method. Finally, use the GA to search for the optimal process parameters. An example of the process parameters design for aTiO2 thin film in the vacuum sput-tering process is tested in this paper.

II. VACUUMSPUTTERINGPROCESS FORTiO2THINFILM A thin-film process contains three sequential steps as follows. A source of film material is first provided, the material is then transported to the substrate, and finally the deposition takes place [10], [15].

In this paper, aTiO2 thin film is formed in the vacuum sputtering process and the quality objective is to focus on its water contact angle. Because theTiO2 thin film has the hydrophilic property, it provides the functions of anti-pollution and self-cleaning. The smaller the water contact angle is, the better the anti-pollution and self-cleaning functions are. The measurement of water contact angle is shown in Fig. 1. The angle is the water contact angle between the line segment and the level surface. The line segment passes through the apex pointa and the pointb on the level surface. There are two main stages to form a TiO2

thin film in the vacuum sputtering process as following:

146 IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, VOL. 7, NO. 1, JANUARY 2010

model. Meanwhile, those parameters are employed to conduct the ex-periment for aTiO2thin film. The water contact angles obtained from the practical experiment at two different positions are 3.83and 4.03. The average angle is 3.93. There is 1.75% difference between 4and 3.93. This result from the model of the proposed procedure is quite promising. In addition, the result is also better than the experimental results ofL18, shown in Table II. Therefore, the proposed procedure is a good approach to obtain better parameters for aTiO₂thin film in the vacuum sputtering process.

VIII. CONCLUSION

This paper presents a design procedure of process parameters by in-tegrating both the modeling and optimization methods. The procedure combines the Taguchi method, the ANN, and the GA to search for the optimal process parameters for aTiO₂ thin film in the vacuum sput-tering process. The OAL18is used to collect experiment data repre-senting the quality performance of aTiO₂ thin film. The Taguchi re-sponse table is used to find the best level combination of factors. Then, the 19 experimental data are collected as the inputs for training the ANN model by using backpropagation algorithms. Further, the better process parameters are searched by the GA. Those process parame-ters are employed to conduct the experiment for aTiO2thin film. The

result is quite promising and better than the results obtained by the Taguchi experimental method usually used in the industry. Therefore, we conclude that the proposed procedure possessing the functions of modeling and optimization can be used to solve the process parameters design problems.

REFERENCES

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2000.

Monitoring of Timed Discrete Events Systems With Interrupts

Adib Allahham and Hassane Alla

Abstract—A framework is introduced for monitoring the interrupting faults in the timed discrete events systems. We introduce the notion of ac-ceptable behavior of the system subjected to these faults: permanent or in-termittent. The acceptable behavior of a system is modeled by a stopwatch automaton. The timed sub-spaces in the locations of the automaton delimit exactly the range of the acceptable behavior. They are synthesized using the techniques of reachability analysis of stopwatch automata in a way to detect the system faults as early as possible.

Note to Practitioners—The final monitoring system is a stopwatch automaton. This automaton can be translated into a Sequential Function Chart (SFC), an industrially recognized and used tool of programming logic controllers (PLCs). Consequently, we can implement the pro-posed monitoring system by the PLC, used extensively in the industrial environment.

Index Terms—Interrupting faults, monitoring, reachability analysis, stopwatch automata, timed discrete events systems.

I. INTRODUCTION

Monitoring the complex systems plays an important role for eco-nomic, security and reliability reasons. It has been received a consid-erable attention in the literature of various domains. In this paper, the monitoring task consists in determining the occurrence of the faults in the systems that can be modeled as timed discrete-event systems (TDES). Our work considers only the intermittent and permanent faults [1] that interrupt the task of a resource. We call these faults inter-rupting faults. System availability relates to some tolerance against the intermittent faults—the capability of a system to execute its tasks even

Manuscript received January 23, 2008; revised July 09, 2008 and October 30, 2008. First published April 24, 2009; current version published January 08, 2010. This paper was recommended for publication by Associate Editor B. Turchiano and Editor Y. Narahari upon evaluation of the reviewers’ comments. The authors are with the Department of Control Systems, GIPSA Lab-oratory, Grenoble University, Saint Martin 38402, France (e-mail: adib.al-lahham@inpg.fr; adiballahham@hotmail.com; Hassane.Alla@inpg.fr).

Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org.

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