Two-Level Factorials (cont.)
|
|
- Corey Fleming
- 5 years ago
- Views:
Transcription
1 EE0H 0 wolevel actorials (cont.) Blocking and Confounding ractional actorials he concept of design Resolution EE0H 0 Blocking What if we need to clean the reactor every four runs? block his block will bias the interaction. he generator is =.
2 EE0H 0 A simple Example in Blocking Do experiments, at levels of b, and estimate the effects of x and x x b x EE0H 0 Blocking What if we need to clean the reactor every two runs? his will bias the, interactions but also the effect!! We used two generators: = (b ) = (b ) = x = = = b b block V V
3 EE0H 0 or two runs/block ( blocks) better to use this blocking: b his blocking will bias the, and We used two generators: = (b ) = (b ) = x = = he main effects are still recognizable! b blck V V Blocking EE0H 0 0 A B C D block Examples on Blocking design ( runs) in blocks of runs: Need one generator: = (i.e. block=)
4 EE0H 0 Examples on Blocking design ( runs) in blocks of runs: Need two generators: B =, B = 0 A B C D B B EE0H 0 Can we measure the effect of the added variable? x x x
5 EE0H 0 Large Experiments have many insignificant Effects... Effects of experiment Residuals after eliminating insignificant effects EE0H 0 Large experiments can be cut to half without significant conflicts... 0
6 EE0H 0 ractional actorials Do need runs to estimate significant parameters? fractional factorial (half fraction) he generating relation is = = = = (=) = = = = avg x0. Since,, and are insignificant, this design works. (his is a resolution design.) EE0H 0 ractional actorial he fractional factorial is a complete factorial for any of the variables! () () () () () () () () () () () () () () () () () () () ()
7 EE0H 0 Combining Half ractions = = = = avg x0. = = = = avg x0. EE0H 0 Designs of "Resolution R" No pfactor confounded with anything less than Rp factors. Example: = is a resolution design. Example: onehalf fractional of the LCVD experiment = => runs! = ( ) eff = 0. = ( ) eff = 0. = ( ) eff = 0. = (Avg 0. ) Avg =. avg
8 EE0H 0 ractional actorial 0 A B C D E EE0H 0 Obtaining the Highest ossible Resolution Write a full factorial for the first k variables Associate the kth variable with / the interaction of the k variables. A fractional factorial of of resolution R contains complete factorials in in every set of of R variables!
9 EE0H 0 Example: Modeling lasma Etch Anisotropy arameter Range Units R ower 0000 Watts ressure 0000 morr Electrode Spacing.. cm CCl low 000 sccm He low 000 sccm O low 00 sccm he original experiment included = runs (plus center point replications). A = quarter fraction was used for anisotropy, because the measurements were costly and noisy. EE0H 0 Example: Designing the quarter fraction 0 = = V Rf r El
10 EE0H 0 ractional factorials can be blocked. Just choose interactions that are unimportant. = = 0 Blocked ractional actorial Experiments Rf r El BBB V EE0H 0 ypical Designs are available... 0
11 EE0H 0 Resolving Ambiguities in ractional actorials Upon the completion of a fractional factorial, selected confoundings can be clarified with selected additional runs. = = Suppose that is significant. Since l = ( ) we need a minimum of additional runs. Because of potential blocking between the main experiment and the supplement, we actually need additional runs. One choice is: Rf r El Results R R R inally, solve the system: M 0.l 0.l 0.l = R M 0.l 0.l 0.l = R M 0.l 0.l 0.l = R l l l = l conf EE0H 0 Conclusion actorial experiments can accommodate blocking, if one controls the conflicts in estimating effects. ractional factorial experiments take advantage of the insignificance of higher order terms, to accommodate many variables with few runs. Experiments can be done in stages, initially screening, and later analyzing important effects in detail. (see chapter in BHH or chapter in Montgomery)
Two-Level Factorials (cont.)
TwoLevel Factorials (cont.) Blocking and Confounding Fractional Factorials The concept of design Resolution 1 EE290H F05 2 What if we need to clean the reactor every four runs? Run 1 2 3 4 5 6 7 8 P T
More informationSession 3 Fractional Factorial Designs 4
Session 3 Fractional Factorial Designs 3 a Modification of a Bearing Example 3. Fractional Factorial Designs Two-level fractional factorial designs Confounding Blocking Two-Level Eight Run Orthogonal Array
More informationTwo Factor Full Factorial Design with Replications
Two Factor Full Factorial Design with Replications Raj Jain Washington University in Saint Louis Saint Louis, MO 63130 Jain@cse.wustl.edu These slides are available on-line at: http://www.cse.wustl.edu/~jain/cse567-08/
More informationTwo-Level Fractional Factorial Design
Two-Level Fractional Factorial Design Reference DeVor, Statistical Quality Design and Control, Ch. 19, 0 1 Andy Guo Types of Experimental Design Parallel-type approach Sequential-type approach One-factor
More informationExperimental design (KKR031, KBT120) Tuesday 11/ :30-13:30 V
Experimental design (KKR031, KBT120) Tuesday 11/1 2011-8:30-13:30 V Jan Rodmar will be available at ext 3024 and will visit the examination room ca 10:30. The examination results will be available for
More information2 k, 2 k r and 2 k-p Factorial Designs
2 k, 2 k r and 2 k-p Factorial Designs 1 Types of Experimental Designs! Full Factorial Design: " Uses all possible combinations of all levels of all factors. n=3*2*2=12 Too costly! 2 Types of Experimental
More information23. Fractional factorials - introduction
173 3. Fractional factorials - introduction Consider a 5 factorial. Even without replicates, there are 5 = 3 obs ns required to estimate the effects - 5 main effects, 10 two factor interactions, 10 three
More informationMultivariate Control and Model-Based SPC
Multivariate Control and Model-Based SPC T 2, evolutionary operation, regression chart. 1 Multivariate Control Often, many variables must be controlled at the same time. Controlling p independent parameters
More information5. Blocking and Confounding
5. Blocking and Confounding Hae-Jin Choi School of Mechanical Engineering, Chung-Ang University 1 Why Blocking? Blocking is a technique for dealing with controllable nuisance variables Sometimes, it is
More informationResponse Surface Methodology
Response Surface Methodology Process and Product Optimization Using Designed Experiments Second Edition RAYMOND H. MYERS Virginia Polytechnic Institute and State University DOUGLAS C. MONTGOMERY Arizona
More informationResponse Surface Methodology:
Response Surface Methodology: Process and Product Optimization Using Designed Experiments RAYMOND H. MYERS Virginia Polytechnic Institute and State University DOUGLAS C. MONTGOMERY Arizona State University
More informationTWO-LEVEL FACTORIAL EXPERIMENTS: BLOCKING. Upper-case letters are associated with factors, or regressors of factorial effects, e.g.
STAT 512 2-Level Factorial Experiments: Blocking 1 TWO-LEVEL FACTORIAL EXPERIMENTS: BLOCKING Some Traditional Notation: Upper-case letters are associated with factors, or regressors of factorial effects,
More informationUNIVERSITY OF CALIFORNIA College of Engineering Department of Electrical Engineering and Computer Sciences. PROBLEM SET No. 5 Official Solutions
1 UNIVERSITY OF CALIFORNIA College of Engineering Department of Electrical Engineering and Computer Sciences C. SPANOS Special Issues in Semiconductor Manufacturing EECS 290H Fall 0 PROBLEM SET No. Official
More informationResponse Surface Methodology IV
LECTURE 8 Response Surface Methodology IV 1. Bias and Variance If y x is the response of the system at the point x, or in short hand, y x = f (x), then we can write η x = E(y x ). This is the true, and
More informationDesign of Engineering Experiments Chapter 8 The 2 k-p Fractional Factorial Design
Design of Engineering Experiments Chapter 8 The 2 k-p Fractional Factorial Design Text reference, Chapter 8 Motivation for fractional factorials is obvious; as the number of factors becomes large enough
More informationESTIMATION METHODS FOR MISSING DATA IN UN-REPLICATED 2 FACTORIAL AND 2 FRACTIONAL FACTORIAL DESIGNS
Journal of Statistics: Advances in Theory and Applications Volume 5, Number 2, 2011, Pages 131-147 ESTIMATION METHODS FOR MISSING DATA IN k k p UN-REPLICATED 2 FACTORIAL AND 2 FRACTIONAL FACTORIAL DESIGNS
More informationHow To: Analyze a Split-Plot Design Using STATGRAPHICS Centurion
How To: Analyze a SplitPlot Design Using STATGRAPHICS Centurion by Dr. Neil W. Polhemus August 13, 2005 Introduction When performing an experiment involving several factors, it is best to randomize the
More information6. Fractional Factorial Designs (Ch.8. Two-Level Fractional Factorial Designs)
6. Fractional Factorial Designs (Ch.8. Two-Level Fractional Factorial Designs) Hae-Jin Choi School of Mechanical Engineering, Chung-Ang University 1 Introduction to The 2 k-p Fractional Factorial Design
More informationSection 3: Etching. Jaeger Chapter 2 Reader
Section 3: Etching Jaeger Chapter 2 Reader Etch rate Etch Process - Figures of Merit Etch rate uniformity Selectivity Anisotropy d m Bias and anisotropy etching mask h f substrate d f d m substrate d f
More informationTMA4267 Linear Statistical Models V2017 (L19)
TMA4267 Linear Statistical Models V2017 (L19) Part 4: Design of Experiments Blocking Fractional factorial designs Mette Langaas Department of Mathematical Sciences, NTNU To be lectured: March 28, 2017
More informationChapter 9 Other Topics on Factorial and Fractional Factorial Designs
Chapter 9 Other Topics on Factorial and Fractional Factorial Designs 許湘伶 Design and Analysis of Experiments (Douglas C. Montgomery) hsuhl (NUK) DAE Chap. 9 1 / 26 The 3 k Factorial Design 3 k factorial
More informationEtching: Basic Terminology
Lecture 7 Etching Etching: Basic Terminology Introduction : Etching of thin films and sometimes the silicon substrate are very common process steps. Usually selectivity, and directionality are the first
More informationST3232: Design and Analysis of Experiments
Department of Statistics & Applied Probability 2:00-4:00 pm, Monday, April 8, 2013 Lecture 21: Fractional 2 p factorial designs The general principles A full 2 p factorial experiment might not be efficient
More informationDesign of Screening Experiments with Partial Replication
Design of Screening Experiments with Partial Replication David J. Edwards Department of Statistical Sciences & Operations Research Virginia Commonwealth University Robert D. Leonard Department of Information
More informationDesign and Analysis of Experiments
Design and Analysis of Experiments Part VII: Fractional Factorial Designs Prof. Dr. Anselmo E de Oliveira anselmo.quimica.ufg.br anselmo.disciplinas@gmail.com 2 k : increasing k the number of runs required
More informationEtching. Etching Terminology. Etching Considerations for ICs. Wet Etching. Reactive Ion Etching (plasma etching) Professor N Cheung, U.C.
Etching Etching Terminology Etching Considerations or ICs Wet Etching Reactie Ion Etching (plasma etching) 1 Etch Process - Figures o Merit Etch rate Etch rate uniormity Selectiity Anisotropy 2 (1) Bias
More informationSoftware Sleuth Solves Engineering Problems
1 Software Sleuth Solves Engineering Problems Mark J. Anderson and Patrick J. Whitcomb Stat-Ease, Inc. 2021 East Hennepin Ave, Suite 191, Minneapolis, MN 55413 Telephone: 612/378-9449, Fax: 612/378-2152
More informationAssignment 9 Answer Keys
Assignment 9 Answer Keys Problem 1 (a) First, the respective means for the 8 level combinations are listed in the following table A B C Mean 26.00 + 34.67 + 39.67 + + 49.33 + 42.33 + + 37.67 + + 54.67
More informationAn Introduction to Design of Experiments
An Introduction to Design of Experiments Douglas C. Montgomery Regents Professor of Industrial Engineering and Statistics ASU Foundation Professor of Engineering Arizona State University Bradley Jones
More informationPlasma modelling & reactor design
Plasma modelling & reactor design Alan Howling, Ben Strahm, Christoh Hollenstein Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland Center for Research in Plasma Physics (CRPP) 1) The "lasma
More informationBLOCK DESIGNS WITH FACTORIAL STRUCTURE
BLOCK DESIGNS WITH ACTORIAL STRUCTURE V.K. Gupta and Rajender Parsad I.A.S.R.I., Library Avenue, New Delhi - 0 0 The purpose of this talk is to expose the participants to the interesting work on block
More informationETCHING Chapter 10. Mask. Photoresist
ETCHING Chapter 10 Mask Light Deposited Substrate Photoresist Etch mask deposition Photoresist application Exposure Development Etching Resist removal Etching of thin films and sometimes the silicon substrate
More informationFractional Factorial Designs
Fractional Factorial Designs ST 516 Each replicate of a 2 k design requires 2 k runs. E.g. 64 runs for k = 6, or 1024 runs for k = 10. When this is infeasible, we use a fraction of the runs. As a result,
More informationOptimize Your Process-Optimization Efforts
1 Optimize Your Process-Optimization Efforts Highly efficient, statistically based methods can identify the vital few factors that affect process efficiency and product quality. Mark J. Anderson and Patrick
More informationAmerican Society for Quality
American Society for Quality The 2k-p Fractional Factorial Designs Part I Author(s): G. E. P. Box and J. S. Hunter Source: Technometrics, Vol. 3, No. 3 (Aug., 1961), pp. 311-351 Published by: American
More informationAnswer Keys to Homework#10
Answer Keys to Homework#10 Problem 1 Use either restricted or unrestricted mixed models. Problem 2 (a) First, the respective means for the 8 level combinations are listed in the following table A B C Mean
More informationTechnology Improvement and Fault TCP Etch Chamber and a Dual Frequency Oxide Etch Chamber
Technology Improvement and Fault Detection @ TCP Etch Chamber and a Dual Frequency Oxide Etch Chamber Russell Benson, Micron Daniel Steckert, Micron Lutz Eichhorn, Plasmetrex Michael Klick, Plasmetrex
More informationFractional Factorial Designs
k-p Fractional Factorial Designs Fractional Factorial Designs If we have 7 factors, a 7 factorial design will require 8 experiments How much information can we obtain from fewer experiments, e.g. 7-4 =
More informationSTAT451/551 Homework#11 Due: April 22, 2014
STAT451/551 Homework#11 Due: April 22, 2014 1. Read Chapter 8.3 8.9. 2. 8.4. SAS code is provided. 3. 8.18. 4. 8.24. 5. 8.45. 376 Chapter 8 Two-Level Fractional Factorial Designs more detail. Sequential
More informationDESIGN AND ANALYSIS OF EXPERIMENTS Third Edition
DESIGN AND ANALYSIS OF EXPERIMENTS Third Edition Douglas C. Montgomery ARIZONA STATE UNIVERSITY JOHN WILEY & SONS New York Chichester Brisbane Toronto Singapore Contents Chapter 1. Introduction 1-1 What
More informationSolution to Final Exam
Stat 660 Solution to Final Exam. (5 points) A large pharmaceutical company is interested in testing the uniformity (a continuous measurement that can be taken by a measurement instrument) of their film-coated
More informationDesign of experiment ERT k-p fractional factorial. Miss Hanna Ilyani Zulhaimi
+ Design of experiment ERT 427 2 k-p fractional factorial Miss Hanna Ilyani Zulhaimi + OUTLINE n Limitation of full factorial design n The concept of fractional factorial, 2 k-p n One-half fraction factorial
More informationThe One-Quarter Fraction
The One-Quarter Fraction ST 516 Need two generating relations. E.g. a 2 6 2 design, with generating relations I = ABCE and I = BCDF. Product of these is ADEF. Complete defining relation is I = ABCE = BCDF
More informationReactive Ion Etching (RIE)
Reactive Ion Etching (RIE) RF 13.56 ~ MHz plasma Parallel-Plate Reactor wafers Sputtering Plasma generates (1) Ions (2) Activated neutrals Enhance chemical reaction 1 2 Remote Plasma Reactors Plasma Sources
More informationStat664 Homework #3 due April 21 Turn in problems marked with
Stat664 Homework #3 due April 2 Turn in problems marked with Note: Whenever appropriate/possible, inspect the possibilities for need of transformation, determine suitable power (considering only power
More informationDOE WEB SEMINAR,
DOE WEB SEMINAR, 2013.03.29 Electron energy distribution function of the plasma in the presence of both capacitive field and inductive field : from electron heating to plasma processing control 1 mm PR
More information4. The 2 k Factorial Designs (Ch.6. Two-Level Factorial Designs)
4. The 2 k Factorial Designs (Ch.6. Two-Level Factorial Designs) Hae-Jin Choi School of Mechanical Engineering, Chung-Ang University Introduction to 2 k Factorial Designs Special case of the general factorial
More informationPrediction of Etch Profile Uniformity Using Wavelet and Neural Network
256 Prediction of Etch Profile Uniformity Using Wavelet and Neural Network Won Sun Choi, Myo Taeg Lim, and Byungwhan Kim * Abstract: Conventionally, profile non-uniformity has been characterized by relying
More informationAssessing the Similarity of Bioanalytical Methods
Assessing the Similarity of Bioanalytical Methods Jason Liao, Ph.D. Merck Research Laboratories Joint work with Yu Tian 00 MBSW Introduction Outline Existing methods & potential problems New method Linear
More informationFractional Replications
Chapter 11 Fractional Replications Consider the set up of complete factorial experiment, say k. If there are four factors, then the total number of plots needed to conduct the experiment is 4 = 1. When
More informationSuppose we needed four batches of formaldehyde, and coulddoonly4runsperbatch. Thisisthena2 4 factorial in 2 2 blocks.
58 2. 2 factorials in 2 blocks Suppose we needed four batches of formaldehyde, and coulddoonly4runsperbatch. Thisisthena2 4 factorial in 2 2 blocks. Some more algebra: If two effects are confounded with
More informationAn Experimental Design Approach
An Experimental Design Approach to Process Design Martha Grover Gallivan School of Chemical & Biomolecular Engineering Georgia Institute of echnology ebruary 11, 2008 actors Influencing Material Properties
More informationFractional Factorials
Fractional Factorials Bruce A Craig Department of Statistics Purdue University STAT 514 Topic 26 1 Fractional Factorials Number of runs required for full factorial grows quickly A 2 7 design requires 128
More informationFRANKLIN-SIMPSON HIGH SCHOOL
FRANKLIN-SIMPSON HIGH SCHOOL Course Name: Physics Unit Name: Speed, Velocity and Acceleration Quality Core Objectives: Unit 1 Speed, Velocity and Acceleration A.1. Scientific Inquiry a. Identify and clarify
More information2D Hybrid Fluid-Analytical Model of Inductive/Capacitive Plasma Discharges
63 rd GEC & 7 th ICRP, 2010 2D Hybrid Fluid-Analytical Model of Inductive/Capacitive Plasma Discharges E. Kawamura, M.A. Lieberman, and D.B. Graves University of California, Berkeley, CA 94720 This work
More information4. Design of Experiments (DOE) (The 2 k Factorial Designs)
4. Design of Experiments (DOE) (The 2 k Factorial Designs) Hae-Jin Choi School of Mechanical Engineering, Chung-Ang University 1 Example: Golfing How to improve my score in Golfing? Practice!!! Other than
More informationE SC 412 Nanotechnology: Materials, Infrastructure, and Safety Wook Jun Nam
E SC 412 Nanotechnology: Materials, Infrastructure, and Safety Wook Jun Nam Lecture 10 Outline 1. Wet Etching/Vapor Phase Etching 2. Dry Etching DC/RF Plasma Plasma Reactors Materials/Gases Etching Parameters
More informationReference: Chapter 6 of Montgomery(8e) Maghsoodloo
Reference: Chapter 6 of Montgomery(8e) Maghsoodloo 51 DOE (or DOX) FOR BASE BALANCED FACTORIALS The notation k is used to denote a factorial experiment involving k factors (A, B, C, D,..., K) each at levels.
More informationEtching Issues - Anisotropy. Dry Etching. Dry Etching Overview. Etching Issues - Selectivity
Etching Issues - Anisotropy Dry Etching Dr. Bruce K. Gale Fundamentals of Micromachining BIOEN 6421 EL EN 5221 and 6221 ME EN 5960 and 6960 Isotropic etchants etch at the same rate in every direction mask
More information8. Sequences, Series, and Probability 8.1. SEQUENCES AND SERIES
8. Sequences, Series, and Probability 8.1. SEQUENCES AND SERIES What You Should Learn Use sequence notation to write the terms of sequences. Use factorial notation. Use summation notation to write sums.
More informationRegression Analysis. Simple Regression Multivariate Regression Stepwise Regression Replication and Prediction Error EE290H F05
Regression Analysis Simple Regression Multivariate Regression Stepwise Regression Replication and Prediction Error 1 Regression Analysis In general, we "fit" a model by minimizing a metric that represents
More informationData Set 1A: Algal Photosynthesis vs. Salinity and Temperature
Data Set A: Algal Photosynthesis vs. Salinity and Temperature Statistical setting These data are from a controlled experiment in which two quantitative variables were manipulated, to determine their effects
More informationLecture 9: Factorial Design Montgomery: chapter 5
Lecture 9: Factorial Design Montgomery: chapter 5 Page 1 Examples Example I. Two factors (A, B) each with two levels (, +) Page 2 Three Data for Example I Ex.I-Data 1 A B + + 27,33 51,51 18,22 39,41 EX.I-Data
More informationSupplementary Information
Supplementary Information Supplementary Figure 1 Raman spectroscopy of CVD graphene on SiO 2 /Si substrate. Integrated Raman intensity maps of D, G, 2D peaks, scanned across the same graphene area. Scale
More informationDefinitive Screening Designs
Definitive Screening Designs Bradley Jones September 2011 Copyright 2008, SAS Institute Inc. All rights reserved. Joint work with Chris Nachtsheim Outline 1. Motivation 2. Design Structure 3. Design Construction
More informationBlocks are formed by grouping EUs in what way? How are experimental units randomized to treatments?
VI. Incomplete Block Designs A. Introduction What is the purpose of block designs? Blocks are formed by grouping EUs in what way? How are experimental units randomized to treatments? 550 What if we have
More information2.830 Homework #6. April 2, 2009
2.830 Homework #6 Dayán Páez April 2, 2009 1 ANOVA The data for four different lithography processes, along with mean and standard deviations are shown in Table 1. Assume a null hypothesis of equality.
More informationEnhanced Chamber Management and Fault Detection in Plasma Etch Processes via SEERS(Self Excited Electron Resonance Spectroscopy)
Enhanced Chamber Management and Fault Detection in Plasma Etch Processes via SEERS(Self Excited Electron Resonance Spectroscopy) *Kye Hyun Baek, Gopyo Lee, Yong Woo Lee, Gyung-Jin Min, Changjin Kang, Han-Ku
More information19. Blocking & confounding
146 19. Blocking & confounding Importance of blocking to control nuisance factors - day of week, batch of raw material, etc. Complete Blocks. This is the easy case. Suppose we run a 2 2 factorial experiment,
More information10.0 REPLICATED FULL FACTORIAL DESIGN
10.0 REPLICATED FULL FACTORIAL DESIGN (Updated Spring, 001) Pilot Plant Example ( 3 ), resp - Chemical Yield% Lo(-1) Hi(+1) Temperature 160 o 180 o C Concentration 10% 40% Catalyst A B Test# Temp Conc
More informationPlasma Etch Tool Gap Distance DOE Final Report
Plasma Etch Tool Gap Distance DOE Final Report IEE 572 Doug Purvis Mei Lee Gallagher 12/4/00 Page 1 of 10 Protocol Purpose: To establish new Power, Pressure, and Gas Ratio setpoints that are acceptable
More informationFormula for the t-test
Formula for the t-test: How the t-test Relates to the Distribution of the Data for the Groups Formula for the t-test: Formula for the Standard Error of the Difference Between the Means Formula for the
More informationEE290H F05. Spanos. Lecture 5: Comparison of Treatments and ANOVA
1 Design of Experiments in Semiconductor Manufacturing Comparison of Treatments which recipe works the best? Simple Factorial Experiments to explore impact of few variables Fractional Factorial Experiments
More informationDOE Wizard Screening Designs
DOE Wizard Screening Designs Revised: 10/10/2017 Summary... 1 Example... 2 Design Creation... 3 Design Properties... 13 Saving the Design File... 16 Analyzing the Results... 17 Statistical Model... 18
More informationGuide to the Expression of Uncertainty in Measurement (GUM)- An Overview
Estimation of Uncertainties in Chemical Measurement Guide to the Expression of Uncertainty in Measurement (GUM)- An Overview Angelique Botha Method of evaluation: Analytical measurement Step 1: Specification
More informationEffect of Noble Gas. Plasma Processing Laboratory University of Houston. Acknowledgements: DoE Plasma Science Center and NSF
Ion Energy Distributions in Pulsed Plasmas with Synchronous DC Bias: Effect of Noble Gas W. Zhu, H. Shin, V. M. Donnelly and D. J. Economou Plasma Processing Laboratory University of Houston Acknowledgements:
More informationPrentice Hall Stats: Modeling the World 2004 (Bock) Correlated to: National Advanced Placement (AP) Statistics Course Outline (Grades 9-12)
National Advanced Placement (AP) Statistics Course Outline (Grades 9-12) Following is an outline of the major topics covered by the AP Statistics Examination. The ordering here is intended to define the
More informationAutoregressive models with distributed lags (ADL)
Autoregressive models with distributed lags (ADL) It often happens than including the lagged dependent variable in the model results in model which is better fitted and needs less parameters. It can be
More informationRESPONSE SURFACE MODELLING, RSM
CHEM-E3205 BIOPROCESS OPTIMIZATION AND SIMULATION LECTURE 3 RESPONSE SURFACE MODELLING, RSM Tool for process optimization HISTORY Statistical experimental design pioneering work R.A. Fisher in 1925: Statistical
More informationEFFECT OF PRESSURE AND ELECTRODE SEPARATION ON PLASMA UNIFORMITY IN DUAL FREQUENCY CAPACITIVELY COUPLED PLASMA TOOLS *
EFFECT OF PRESSURE AND ELECTRODE SEPARATION ON PLASMA UNIFORMITY IN DUAL FREQUENCY CAPACITIVELY COUPLED PLASMA TOOLS * Yang Yang a) and Mark J. Kushner b) a) Department of Electrical and Computer Engineering
More informationDo you share more genes with your mother or your father?
Do you share more genes with your mother or your father? By Madeleine Beekman, The Conversation on 12.07.17 Word Count 818 Level MAX Mothers play a big role in our genetic makeup. All mitochondrial DNA
More informationLecture 6 Plasmas. Chapters 10 &16 Wolf and Tauber. ECE611 / CHE611 Electronic Materials Processing Fall John Labram 1/68
Lecture 6 Plasmas Chapters 10 &16 Wolf and Tauber 1/68 Announcements Homework: Homework will be returned to you on Thursday (12 th October). Solutions will be also posted online on Thursday (12 th October)
More informationReference: CHAPTER 7 of Montgomery(8e)
Reference: CHAPTER 7 of Montgomery(8e) 60 Maghsoodloo BLOCK CONFOUNDING IN 2 k FACTORIALS (k factors each at 2 levels) It is often impossible to run all the 2 k observations in a 2 k factorial design (or
More informationUnit 9: Confounding and Fractional Factorial Designs
Unit 9: Confounding and Fractional Factorial Designs STA 643: Advanced Experimental Design Derek S. Young 1 Learning Objectives Understand what it means for a treatment to be confounded with blocks Know
More informationPlasma etch control by means of physical plasma parameter measurement with HERCULES Sematech AEC/APC Symposium X
Plasma etch control by means of physical plasma parameter measurement with HERCULES A. Steinbach F. Bell D. Knobloch S. Wurm Ch. Koelbl D. Köhler -1- Contents - Introduction - Motivation - Plasma monitoring
More informationTesting methodology. It often the case that we try to determine the form of the model on the basis of data
Testing methodology It often the case that we try to determine the form of the model on the basis of data The simplest case: we try to determine the set of explanatory variables in the model Testing for
More informationRESPONSE SURFACE METHODOLOGY
RESPONSE SURFACE METHODOLOGY WILEY SERIES IN PROBABILITY AND STATISTICS Established by WALTER A. SHEWHART and SAMUEL S. WILKS Editors: David J. Balding, Noel A. C. Cressie, Garrett M. Fitzmaurice, Iain
More informationResponse Surface Methodology: Process and Product Optimization Using Designed Experiments, 3rd Edition
Brochure More information from http://www.researchandmarkets.com/reports/705963/ Response Surface Methodology: Process and Product Optimization Using Designed Experiments, 3rd Edition Description: Identifying
More informationVladimir Spokoiny Design of Experiments in Science and Industry
W eierstraß-institut für Angew andte Analysis und Stochastik Vladimir Spokoiny Design of Experiments in Science and Industry www.ndt.net/index.php?id=8310 Mohrenstr. 39, 10117 Berlin spokoiny@wias-berlin.de
More informationSupplementary Information. Atomic Layer Deposition of Platinum Catalysts on Nanowire Surfaces for Photoelectrochemical Water Reduction
Supplementary Information Atomic Layer Deposition of Platinum Catalysts on Nanowire Surfaces for Photoelectrochemical Water Reduction Neil P. Dasgupta 1 ǂ, Chong Liu 1,2 ǂ, Sean Andrews 1,2, Fritz B. Prinz
More informationSizing Mixture (RSM) Designs for Adequate Precision via Fraction of Design Space (FDS)
for Adequate Precision via Fraction of Design Space (FDS) Pat Whitcomb Stat-Ease, Inc. 61.746.036 036 fax 61.746.056 pat@statease.com Gary W. Oehlert School of Statistics University it of Minnesota 61.65.1557
More informationImproving the Efficiency and Efficacy of Controlled Sequential Bifurcation for Simulation Factor Screening
Improving the Efficiency and Efficacy of Controlled Sequential Bifurcation for Simulation Factor Screening Hong Wan School of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, USA,
More information2.830J / 6.780J / ESD.63J Control of Manufacturing Processes (SMA 6303) Spring 2008
MIT OpenCourseWare http://ocw.mit.edu 2.830J / 6.780J / ESD.63J Control of Processes (SMA 6303) Spring 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.
More informationARGON RF PLASMA TREATMENT OF PET FILMS FOR SILICON FILMS ADHESION IMPROVEMENT
Journal of Optoelectronics and Advanced Materials Vol. 7, No. 5, October 2005, p. 2529-2534 ARGON RF PLASMA TREATMENT OF FILMS FOR SILICON FILMS ADHESION IMPROVEMENT I. A. Rusu *, G. Popa, S. O. Saied
More informationModeling of Process Plasma Using a Radial Basis Function Network: A Case Study
68 ICASE: The Institute of Control, Automation and Systems Engineers, KOREA Vol., No. 4, December, 000 Modeling of Process Plasma Using a Radial Basis Function Network: A Case Study Byungwhan Kim and Sungjin
More informationCHAPTER 2 AN OVERVIEW OF TCAD SIMULATOR AND SIMULATION METHODOLOGY
15 CHAPTER 2 AN OVERVIEW OF TCAD SIMULATOR AND SIMULATION METHODOLOGY In this chapter TCAD and the various modules available in the TCAD simulator have been discussed. The simulation methodologies to extract
More informationEE C245 ME C218 Introduction to MEMS Design
EE C45 ME C18 Introduction to MEMS Design Fall 008 Prof. Clark T.-C. Nguyen Dept. of Electrical Engineering & Computer Sciences University of California at Berkeley Berkeley, CA 9470 Lecture 6: Output
More informationPractice 2SLS with Artificial Data Part 1
Practice 2SLS with Artificial Data Part 1 Yona Rubinstein July 2016 Yona Rubinstein (LSE) Practice 2SLS with Artificial Data Part 1 07/16 1 / 16 Practice with Artificial Data In this note we use artificial
More informationConfounding and Fractional Replication in Factorial Design
ISSN -580 (Paper) ISSN 5-05 (Online) Vol.6, No.3, 016 onfounding and Fractional Replication in Factorial esign Layla. hmed epartment of Mathematics, ollege of Education, University of Garmian, Kurdistan
More informationUniversity of California, Santa Barbara Santa Barbara, California 93106
HIGH-ASPECT-RATIO INDUCTIVELY COUPLED PLASMA ETCHING OF BULK TITANIUM FOR MEMS APPLICATIONS E. R. Parker 1, M. F. Aimi 2, B. J. Thibeault 3, M. P. Rao 1, and N. C. MacDonald 1,2 1 Mechanical and Environmental
More information