Draper & Guttman (1997) 中說明對於交絡2^{k}因子設計於2^{k-1}個區集(或交絡2^{k-p}部份因子設計於2^{k-p-1}個區集)，需要k(或k-p)個重複實驗方使得每一效應(或能被估的效應)的資訊都能得到。在第一章，我們首先嚴格證明交絡2^{k}因子設計於2^{b}個區集的情況，其中b介於0與k間。然後將它推廣到更一般的情形，即交絡s^{k}因子設計於s^{b}個區集，需要[k/(k-b)]個重複實驗方使得每一效應(或能被估的效應)的資訊都能得到。透過嚴格證明，我們能更清楚看到為何這結果是對的。同時，我們也討論Draper & Guttman (1997) 中提及的例子的缺失。

在第二章，我們利用ANOVA的技巧，探討電磁波干擾之檢定流程。我們共檢測了三種從市場中購買的電子產品，分別為數據機，螢幕及筆記型電腦。透過此實驗，我們可看出目前所採用的標準檢定流程，並無法真正有效控制電磁波干擾所造成的問題。最後，我們也提出檢定流程的建議修正方式。修正後的檢定流程將更有效的控 制電磁波干擾所造成的問題。

Draper and Guttman (1997) show that for basic
2^{k-p}designs, p >= 0, k-p replicates of blocks designs of size two are needed to estimate all the usual (estimable) effects. In Chapter 1, we provide an algebraic formal proof for the two-level blocks designs results and present results applicable to the general case; that is, for the case of s^{k} factorial (p=0) or s^{k-p}ractional factorial (p>0) designs in s^{b} blocks, where 0<b<k-p, at least (k-p)/(k-p-b) replicates are needed to clear up all possible effects. Through the theoretical development presented in this work, it can provide a clearer view on why those results would hold. We will also discuss the estimation equations given in Draper and Guttman (1997).

In Chapter 2, we present a methodology for analyzing the variability of the radiated emission testings of electronic, elecommunication and information technology equipment based on a
modified analysis of variance (ANOVA), with polynomial regression analysis. In our study, three electronic products; modem, monitor and notebook bought from the market are tested. Through the experiment, we show that the international standard fails to provide a methodology which gives control limits for EMC when the electronic products in question are produced. We feel that an improved EMC control procedure presented here can better meet the
needs of radiated emission control.

Contents

Abstract ...................................................................iv

1 s^{k-p} fractional factorial designs in s^{b} blocks....................1
1.1 Introduction............................................................1
1.2 The minimum number of replicates needed to clear up all the effects.....2 1.2.1 Two-level..............................................................2
1.2.2 Prime s-level..........................................................7
1.2.3 The other s-level......................................................7
1.3 Estimation of mean effects under block influence.........................9
1.4 Conclusion..............................................................11
References I................................................................12
2 Inspection plan for radiated emission testing
of information technology equipment.......................................13
2.1 Introduction............................................................13
2.2 Response correlation analysis...........................................16
2.3 Statistical analysis of the fixed effects model.........................18
2.4 Extreme values response curve...........................................23
2.5 Discussion..............................................................25
References II...............................................................28
Appendix....................................................................29

Part I:
[1] Bailey R. A. (1977). Patterns of Confounding in Factorial Designs
Biometrika, 64, 597-604.
[2] Box G. E. P., Hunter W.G. and Hunter J. S. (1978). Statistics for
Experiments, John Wiley & Sons Inc, New York.
[3] Cochran W G and Cox G M (1957). Experimental Designs. 2nd Edition.
John Wiley, New York.
[4] Draper N. R. and Guttman I. (1997). Two-Level Factorial and
Fractional Factorial Designs in Blocks of Size Two.
Journal of Quality Technology}, 29, 71-75.
[5] Fraleigh J. B. and Beauregard R. A. (1995). Linear Algebra, 3rd Edition.
Addison Wesley Publishin Company Inc, New York.
[6] Gallian J. A. (1994). Contemporary Abstract Algebra, 3rd Edition.
D. C. Heath and Company, Toronto.
[7] Montgomery D. C. (1997). Design and Analysis of Experiments, 4th Edition.
John Wiley & Sons Inc, New York.
[8] Wu C. F. J. and Hamada M. (2000). Experiments.
John Wiley & Sons Inc, New York.

Part II:
[1] Draper N. R. and Smith H. (1981). Applied Regression Analysis, 2nd Edition.
John Wiley & Sons Inc, New York.
[2] Montgomery D. C. (1997). Design and Analysis of Experiments, 4th Edition.
John Wiley & Sons Inc, New York.
[3] Neter J., Kutner M. H., Nachtsheim C. J., and Wasserman W. (1999).
Applied Linear Regression Models, 3rd Edition.
The McGraw-Hill Companies, Inc.
[4] Rencher A. C. (1995). Methods of Multivariate Analysis.
John Wiley & Sons Inc, New York.
[5] Wang D.-Y., Lin K.-H., Huang M.-N. L., and Hong J.-J. (2001).
Variability Studies on EMI Data for Electronic,
Telecommunication and Information Technology Equipment.
Manuscript, Department of Electrical Engineering,
National Sun Yat-sen University, Kaohsiung, Taiwan.