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 Statistical Methods in Video Processing Workshop (2004 : Prague, Czech Republic)
 Berlin ; New York : Springer, 2004.
 Description
 Book — viii, 198 : ill. ; 24 cm.
 Summary

This book constitutes the thoroughly refereed postproceedings of the Second International Workshop on Statistical Methods in Video Processing, SMVP 2004, held in Prague, Czech Republic in May 2004 as an ECCV 2004 workshop.The 17 revised full papers presented were carefully selected and improved during two rounds of reviewing and revision. The papers are organized in topical sections on 3D geometry, tracing, background modeling, and image and video analysis.
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2. Multivariate statistical process control with industrial applications [electronic resource] [2002]
 Mason, Robert L. (Robert Lee), 1946
 Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 2002.
 Description
 Book — 1 electronic text (xiii, 263 p.) : ill., digital file.
 Summary

 Preface
 1. Introduction to the T2 Statistic
 2. Basic Concepts about the T2 Statistic
 3. Checking Assumptions for Using a T2 Statistic
 4. Construction of Historical Data Set
 5. Charting the T2 Statistic in Phase I
 6. Charting the T2 Statistic in Phase II
 7. Interpretation of T2 Signals for Two Variables
 8. Interpretation of T2 Signals for the General Case
 9. Improving the Sensitivity of the T2 Statistic
 10. Autocorrelation in T2 Control Charts
 11 The T2 Statistic and Batch Processes Appendix. Distribution Tables Bibliography Index.
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 Montgomery, Douglas C.
 2nd ed.  New York : Wiley, ©1991.
 Description
 Book — 1 volume (various pagings) : illustrations ; 26 cm
 Summary

 Quality Assurance in the Modern Business Environment STATISTICAL METHODS USEFUL IN QUALITY IMPROVEMENT: Modeling Process Quality Inferences about Process Quality STATISTICAL PROCESS CONTROL: Methods and Philosophy of Statistical Process Control Control Charts for Attributes Control Charts for Variables CumulativeSum and ExponentiallyWeighted MovingAverage Control Charts Other Statistical ProcessControl Techniques ProcessCapability Analysis Economic Design of Control Charts PROCESS IMPROVEMENT WITH DESIGNED EXPERIMENTS: The Fundamentals of Experimental Design Factorial Experiments and Other Methods for Process Improvement ACCEPTANCE SAMPLING: LotbyLot Acceptance Sampling for Attributes Acceptance Sampling by Variables Other AcceptanceSampling Procedures.
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TS156 .M64 1991  Available 
 Czitrom, Veronica.
 Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 1997.
 Description
 Book — 1 electronic text (xxvii, 514 p.) : ill., digital file.
 Summary

 Foreword, Preface, Acknowledgments, Introduction, Facts About SEMATECH, SEMATECH Qualification Plan, Part One: GAUGE STUDIES,
 Chapter 1: Introduction to Gauge Studies,
 Chapter 2: Prometrix RS35e Gauge Study in Five TwoLevel Factors and One ThreeLevel Factor,
 Chapter 3: Calibration of an FTIR Spectrometer for Measuring Carbon,
 Chapter 4: Revelation of a Microbalance WarmUp Effect,
 Chapter 5: GRR Methodology for Destructive Testing and Quantitative Assessment of Gauge Capability For OneSide Specifications, Part Two: PASSIVE DATA COLLECTION,
 Chapter 6: Introduction to Passive Data Collection,
 Chapter 7: Understanding the Nature of Variability in a Dry Etch Process,
 Chapter 8: Virgin Versus Recycled Wafers for Furnace Qualification: Is the Expense Justified?,
 Chapter 9: Identifying Sources of Variation in a Wafer Planarization Process,
 Chapter 10: Factors Which Affect the Number of Aerosol Particles Released by Clean Room Operators,
 Chapter 11: A SkipLot Sampling Plan Based on Variance Components for Photolithographic Registration Measurements,
 Chapter 12: Sampling to Meet a Variance Specification: Clean Room Qualification,
 Chapter 13: Snapshot: A Plot Showing Progress Through a Device Development Laboratory, Part Three: DESIGN OF EXPERIMENTS,
 Chapter 14: Introduction To Design Of Experiments,
 Chapter 15: Elimination of TiN Peeling During Exposure to CVD Tungsten Deposition Process Using Designed Experiments,
 Chapter 16: Modeling a Uniformity BullsEye Inversion,
 Chapter 17: Using Fewer Wafers to Resolve Confounding in Screening Experiments,
 Chapter 18: Planarization by Chemical Mechanical Polishing: A Rate and Uniformity Study,
 Chapter 19: Use of Experimental Design to Optimize a Process for Etching Polycrystalline Silicon Gates,
 Chapter 20: Optimization of a Wafer Stepper Alignment System Using Robust Design,
 Chapter 21: Application of SemiEmpirical Model Building to the RTCVD of Polysilicon, Part Four: STATISTICAL PROCESS CONTROL,
 Chapter 22: Introduction to Statistical Process Control,
 Chapter 23: Removing Drift Effects When Calculating Control Limits,
 Chapter 24: Implementation of a Statistical Process Control Capability Strategy in the Manufacture of Raw Printed Circuit Boards for Surface Mount Technology,
 Chapter 25: Obtaining and Using Statistical Process Control Limits in the Semiconductor Industry, Part Five: EQUIPMENT RELIABILITY,
 Chapter 26: Introduction to Equipment Reliability,
 Chapter 27: Marathon Report for a Photolithography Exposure Tool,
 Chapter 28: Experimentation for Equipment Reliability Improvement,
 Chapter 29: How to Determine ComponentBased Preventive Maintenance Plans, Part Six: COMPREHENSIVE CASE STUDY,
 Chapter 30: Introduction to Comprehensive Case Study,
 Chapter 31: Characterization of a Vertical Furnace Chemical Vapor Deposition (CVD) Silicon Nitride Process, Appendix: Introduction to Integrated Circuit Manufacturing, Glossary of Selected Statistical Terms, Index of Selected Statistical Terms.
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 Grous, Ammar.
 11th ed.  London : ISTE : Wiley, 2013.
 Description
 Book — 1 online resource (290 p.)
 Summary

This third book of a 3volume set on Fracture Mechanics adds a pragmatic and supportive character to the previous volumes by focusing on case studies using corrected exercises that teachers, students or engineers will find extremely useful. Due to the wide themes approached in this series, it can also be used to organize work in this field in a new way, as well as in the maintenance of industrial plants.Several cases of sampling plans and their applications in industry are presented, as well as several solved case studies on the main indicators of capability according to ISO/TS 16949,
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 Gibbs, Bruce. P., 1946
 Hoboken, N.J. : Wiley, ©2011.
 Description
 Book — 1 online resource (xx, 605 pages) : illustrations
 Summary

 PREFACE.
 1 INTRODUCTION. 1.1 The Forward and Inverse Modeling Problem. 1.2 A Brief History of Estimation. 1.3 Filtering, Smoothing , and Prediction. 1.4 Prerequisites. 1.5 Notation. 1.6 Summary.
 2 SYSTEM DYNAMICS AND MODELS. 2.1 DiscreteTime Models. 2.2 ContinuousTime Dynamic Models. 2.3 Computation of State Transition and Process Noise Matrices. 2.4 Measurement Models. 2.5 Simulating Stochastic Systems. 2.6 Common Modeling Errors and System Biases. 2.7 Summary.
 3 MODELING EXAMPLES. 3.1 AngleOnly Tracking of Linear Target Motion. 3.2 Maneuvering Vehicle Tracking. 3.3 Strapdown Inertial Navigation System (INS) Error Model. 3.4 Spacecraft Orbit Determination (OD). 3.5 FossilFueled Power Plant. 3.6 Summary.
 4 LINEAR LEASTSQUARES ESTIMATION: FUNDAMENTALS. 4.1 LeastSquares Data Fitting. 4.2 Weighted Least Squares. 4.3 Bayesian Estimation. 4.4 Probabilistic ApproachesMaximum Likelihood and Maximum A Posteriori. 4.5 Summary of Linear Estimation Approaches.
 5 LINEAR LEASTSQUARES ESTIMATION: SOLUTION TECHNIQUES. 5.1 Matrix Norms, Condition Number, Observability, and the PseudoInverse. 5.2 Normal Equation Formation and Solution. 5.3 Orthogonal Transformations and the QR Method. 5.4 LeastSquares Solution Using the SVD. 5.5 Iterative Techniques. 5.6 Comparison of Methods. 5.7 Solution Uniqueness, Observability, and Condition Number. 5.8 PseudoInverses and the Singular Value Transformation (SVD). 5.9 Summary.
 6 LEASTSQUARES ESTIMATION: MODEL ERRORS AND MODEL ORDER. 6.1 Assessing the Validity of the Solution. 6.2 Solution Error Analysis. 6.3 Regression Analysis for Weighted Least Squares. 6.4 Summary.
 7 LEASTSQUARES ESTIMATION: CONSTRAINTS, NONLINEAR MODELS, AND ROBUST TECHNIQUES. 7.1 Constrained Estimates. 7.1.1 LeastSquares with Linear Equality Constraints (Problem LSE). 7.1.2 LeastSquares with Linear Inequality Constraints (Problem LSI). 7.2 Recursive Least Squares. 7.3 Nonlinear Least Squares. 7.4 Robust Estimation. 7.5 Measurement Preprocessing. 7.6 Summary.
 8 KALMAN FILTERING. 8.1 DiscreteTime Kalman Filter. 8.2 Extensions of the Discrete Filter. 8.3 ContinousTime KalmanBucy Filter. 8.4 Modifi cations of the Discrete Kalman Filter. 8.5 SteadyState Solution. 8.6 Wiener Filter. 8.7 Summary.
 9 FILTERING FOR NONLINEAR SYSTEMS, SMOOTHING, ERROR ANALYSIS/MODEL DESIGN, AND MEASUREMENT PREPROCESSING. 9.1 Nonlinear Filtering. 9.2 Smoothing. 9.3 Filter Error Analysis and ReducedOrder Modeling. 9.4 Measurement Preprocessing. 9.5 Summary.
 10 FACTORED (SQUAREROOT) FILTERING. 10.1 Filter Numerical Accuracy. 10.2 UD Filter. 10.3 Square Root Information Filter (SRIF). 10.4 Inertial Navigation System (INS) Example Using Factored Filters. 10.5 Large Sparse Systems and the SRIF. 10.6 Spatial Continuity Constraints and the SRIF Data Equation. 10.7 Summary.
 11 ADVANCED FILTERING TOPICS. 11.1 Maximum Likelihood Parameter Estimation. 11.2 Adaptive Filtering. 11.3 Jump Detection and Estimation. 11.4 Adaptive Target Tracking Using Multiple Model Hypotheses. 11.5 Constrained Estimation. 11.6 Robust Estimation: H Infinity Filters. 11.7 Unscented Kalman Filter (UKF). 11.8 Particle Filters. 11.9 Summary.
 12 EMPIRICAL MODELING . 12.1 Exploratory Time Series Analysis and System Identification. 12.2 Spectral Analysis Based on the Fourier Transform. 12.3 Autoregressive Modeling. 12.4 ARMA Modeling. 12.5 Canonical Variate Analysis. 12.6 Conversion from Discrete to Continuous Models. 12.7 Summary. APPENDIX A SUMMARY OF VECTOR/MATRIX OPERATIONS. APPENDIX B PROBABILITY AND RANDOM VARIABLES. BIBLIOGRAPHY. INDEX.
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 Pripp, Are Hugo.
 New York, NY : Springer, c2013.
 Description
 Book — 1 online resource : ill.
 Summary

 Statistics in Food Science and Nutrition
 Methods and Principles of Statistical Analysis
 Applying Statistics to Food Quality
 Nutritional Epidemiology and Health Effects of Foods
 Application of Multivariate Analysis: Benefits and Pitfalls.
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 Scheirer, Walter J., author.
 [San Rafael, California] : Morgan & Claypool, 2017.
 Description
 Book — 1 PDF (xv, 115 pages).
 Summary

 * Preface* Acknowledgments* Figure Credits* Extrema and Visual Recognition* A Brief Introduction to Statistical Extreme Value Theory* Postrecognition Score Analysis* Recognition Score Normalization* Calibration of Supervised Machine Learning Algorithms* Summary and Future Directions* Bibliography* Author's Biography.
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 IEEE Statistical Signal Processing Workshop (19th : 2016 : Palma de Mallorca, Spain)
 Piscataway, NJ : IEEE, [2016]
 Description
 Book — 1 online resource (various pagings) : illustrations (some color
 Summary

The SSP workshop aims at bringing together researchers form the academia and the industry working on the theory and applications of statistically intensive methods for the processing of signals and data. The potential audience includes not only engineers, but also applied mathematicians, statisticians and physicists that apply statistical algorithms in their respective fields Contributions ranging from the theoretical aspects of algorithm design and analysis to applications to real world problems are encouraged.
10. ... IEEE Statistical Signal Processing Workshop [  2013]
 IEEE Statistical Signal Processing Workshop.
 Piscataway, NJ : Institute of Electrical and Electronic Engineers Red Hook, NY : Available from Curran Associates
 Description
 Journal/Periodical
11. The certified six sigma black belt handbook [2009]
 Kubiak, T. M.
 2nd ed.  Milwaukee, Wis. : ASQ Quality Press, ©2009.
 Description
 Book — 1 online resource (xxvii, 620 pages) : illustrations
 Summary

 Part I: Enterprisewide deployment: Enterprisewide view ; Leadership
 Part II: Organizational process management and measures: Impact on stakeholders ; Critical to x (CTx) requirements ; Benchmarking ; Business performance measures ; Financial measures
 Part III: Team management: Team formation ; Team facilitation ; Team dynamics ; Time management for teams ; Team decisionmaking tools ; Management and planning tools ; Team performance evaluation and reward
 Part IV: Define: Voice of the customer ; Project charter ; Project tracking
 Part V: Measure: Process characteristics ; Data collection ; Measurement systems ; Basic statistics ; Probability ; Process capability
 Part VI: Analyze: Measuring and modeling relationships between variables ; Hypothesis testing ; Failure Mode and Effects Analysis (FMEA) ; Additional analysis methods
 Part VII: Improve: Design of Experiments (DOE) ; Waste elimination ; Cycletime reduction ; Kaizen and Kaizen Blitz Theory of Constraints (TOC) ; Implementation ; Risk analysis and mitigation
 Part VIII: Control: Statistical Process Control (SPC) ; Other control tools ; Maintain controls ; Sustain improvements
 Part IX: Design for Six Sigma (DFSS frameworks and methodologies: Common DFSS methodologies ; Design for X (DFX) ; Robust design and process ; Special design tools.
12. The certified Six Sigma black belt handbook [2017]
 Kubiak, T. M., author.
 Third edition.  Milwaukee, Wisconsin : ASQ Quality Press, 2017.
 Description
 Book — 1 online resource (xxxvii, 908 pages) : illustrations, 1 online resource (1 CDROM (4 3/4 in.)
 Online
13. The Six sigma handbook [2003]
 Pyzdek, Thomas.
 Rev. and expanded ed.  [New York] : McGrawHill, ©2003.
 Description
 Book — 1 online resource (xviii, 813 pages) : illustrations
 Summary

 pt. I. Six Sigma Implementation and Management
 Ch.
 1. Building the Six Sigma Infrastructure
 Ch.
 2. Six Sigma Goals and Metrics
 Ch.
 3. Creating CustomerDriven Organizations
 Ch.
 4. Training for Six Sigma
 Ch.
 5. Six Sigma Teams
 Ch.
 6. Selecting and Tracking Six Sigma Projects
 pt. II. Six Sigma Tools and Techniques
 Ch.
 7. Introduction to DMAIC and Other Improvement Models
 Ch.
 8. Problem Solving Tools
 Ch.
 9. Basic Principles of Measurement
 Ch.
 10. Measurement Systems Analysis
 Ch.
 11. Knowledge Discovery
 Ch.
 12. Statistical Process Control Techniques
 Ch.
 13. Process Capability Analysis
 Ch.
 14. Statistical Analysis of Cause and Effect
 Ch.
 15. Managing Six Sigma Projects
 Ch.
 16. Risk Assessment
 Ch.
 17. Design of Experiments (DOE)
 Ch.
 18. Maintaining Control After the Project
 Ch.
 19. Design for Six Sigma (DFSS)
 Ch.
 20. Lean Manufacturing and Six Sigma.
14. The Certified Six Sigma Yellow Belt Handbook [2016]
 Ramu, Govindarajan.
 Milwaukee : ASQ Quality Press, 2016.
 Description
 Book — 1 online resource (264 pages)
 Summary

 Preface; Acknowledgments; Introduction: The ASQ Certification Process; Part I; Six Sigma Fundamentals; Chapter 1; A. Six Sigma Foundations and Principles; Purpose of Six Sigma: Reducing Variation; Methodology (DMAIC); Evolution of Six Sigma from Quality; Value of Six Sigma to the Organization as a Whole; Chapter 2; B. Lean Foundations and Principles; Purpose of Lean; Lean Methodologies; Value of Lean to the Organization; Chapter 3; C. Six Sigma Roles and Responsibilities; Chapter 4; D. Team Basics;
 1. Types of Teams;
 2. Stages of Development;
 3. DecisionMaking Tools;
 4. Communication Methods.
 Chapter 5E. Quality Tools and Six Sigma Metrics;
 1. Quality Tools;
 2. Six Sigma Metrics; Part II; Define Phase; Chapter 6; A. Project Identification;
 1. Voice of the Customer;
 2. Project Selection;
 3. Stakeholder Analysis;
 4. Process Inputs and Outputs; Chapter 7; B. Project Management (PM) Basics;
 1. Project Charter;
 2. Communication Plan;
 3. Project Planning;
 4. Project Management Tools;
 5. Phase Reviews; Part III; Measure Phase; Chapter 8; A. Basic Statistics; Chapter 9; B. Data Collection;
 1. Data Collection Plans;
 2. Qualitative and Quantitative Data;
 3. Data Collection Techniques.
 Chapter 10C. Measurement System Analysis (MSA);
 1. MSA Terms;
 2. Gauge Repeatability & Reproducibility (GR & R); Part IV; Analyze Phase; Chapter 11; A. Process Analysis Tools;
 1. Lean Tools;
 2. Failure Mode and EffectS Analysis (FMEA); Chapter 12; B. Root Cause Analysis;
 5 Whys or WhyWhy Analysis; Process Mapping; Force Field Analysis; Matrix Charts; Chapter 13; C. Data Analysis;
 1. Basic Distribution Types;
 2. Common and Special Cause Variation; Chapter 14; D. Correlation and Regression;
 1. Correlation;
 2. Regression; Chapter 15; E. Hypothesis Testing; Part V; Improve and Control Phases.
 Chapter 16A. Improvement Techniques;
 1. Kaizen and Kaizen Blitz;
 2. PlanDoCheckAct (PDCA) Cycle;
 3. CostBenefit Analysis; Chapter 17; B. Control Tools and Documentation;
 1. Control Plan;
 2. Control Charts;
 3. Document Control; Part VI; Appendices; Appendix A; ASQ Code of Ethics; Appendix B; ASQ Certified Six Sigma Yellow Belt (CSSYB) Body of Knowledge (2014); Appendix C; ASQ BoK Comparison; Appendix D; Control Limit Formulas; Appendix E; Constants for Control Charts; Appendix F; Areas under Standard Normal Curve; Appendix G; Binomial Distribution; Appendix H; Values of the tDistribution.
 Appendix IAcronym List; Glossary; Bibliography.
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15. The certified six sigma green belt handbook [2015]
 Munro, Roderick A.
 Second edition.  Milwaukee, Wisconsin : ASQ Quality Press, 2015.
 Description
 Book — 1 online resource (xxvi, 600 pages) : illustrations.
 Online
16. The certified six sigma green belt handbook [2008]
 Milwaukee, Wis. : ASQ Quality Press, ©2008.
 Description
 Book — 1 online resource (xxxvi, 443 pages) : illustrations
 Summary

 TABLE OF CONTENTS
 Six sigma and organizational goals
 Lean principles in the organization
 Design for six sigma (DFSS) in the organization
 Process management for projects
 Project management basics
 Management and planning tools
 Business results for projects
 Team dynamics and performance
 Commonly used define phase tools
 Process analysis and documentation
 Probability and statistics
 Collecting and summarizing data
 Probability distributions
 Measurement system analysis
 Process capability and performance
 Exploratory data analysis
 Hypothesis testing
 Design of experiments (DOE)
 Statistical process control (SPC)
 Implement and validate solutions
 Control plan.
 Online
17. Frontiers in statistical quality control 12 [2018]
 Cham : Springer, 2018.
 Description
 Book — 1 online resource. Digital: text file; PDF.
 Summary

 Chapter 1. Phase I DistributionFree Analysis with the R Package dfphase1.
 Chapter 2. Assessment of Shewhart Control Chart Limits in Phase I Implementations under Various Shift and Contamination Scenarios.
 Chapter 3. New results for twosided CUSUMShewhart control charts.
 Chapter 4. Optimal Design of the ShiryaevRoberts Chart: Give Your ShiryaevRoberts a Headstart.
 Chapter 5. On ARLunbiased charts to monitor the traffic intensity of a single server queue.
 Chapter 6. RiskAdjusted Exponentially Weighted Moving Average Charting Procedure Based on MultiResponses.
 Chapter 7. A Primer on SPC and Web Data.
 Chapter 8. The VariableDimension Approach in Multivariate SPC.
 Chapter 8. Distribution Free Bivariate Monitoring of Dispersion.
 Chapter 9. Monitoring and diagnosis of causal relationships among variables.
 Chapter 10. Statistical monitoring of multistage processes.
 Chapter 11. Control Charts for TimeDependent Categorical Processes.
 Chapter 12. Monitoring of short series of dependent observations using a XWAM control chart.
 Chapter 13. Challenges in Monitoring NonStationary Time Series.
 Chapter 14. Design of Experiments: A Key to Successful Innovation.
 Chapter 15. DOptimal ThreeStage Unbalanced Nested Designs for the Determination of Measurement Precision.
 Chapter 16. Sampling inspection by variables under Weibull distribution and Type I censoring.
 Chapter 17. Approximate Loglinear Cumulative Exposure Time Scale Model by Joint Moment Generating Function of Covariates.
 Chapter 18. A Critique of Bayesian Approaches within Quality Improvement.
 Chapter 19. A Note on the Quality of Biomedical Statistics.
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18. Statistical design and analysis of experiments : with applications to engineering and science [2003]
 Mason, Robert L. (Robert Lee), 1946
 2nd ed.  Hoboken, N.J. : J. Wiley, c2003.
 Description
 Book — xix, 728 p. : ill. ; 25 cm.
 Summary

 Preface. PART I: FUNDAMENTAL STATISTICAL CONCEPTS. Statistics in Engineering and Science. Fundamentals of Statistical Inference. Inferences on Means and Standard Deviations. PART II: DESIGN AND ANALYSIS WITH FACTORIAL STRUCTURE. Statistical Principles in Experimental Design. Factorial Experiments in Completely Randomized Designs. Analysis of Completely Randomized Designs. Fractional Factorial Experiments. Analysis of Fractional Factorial Experiments. PART III: DESIGN AND ANALYSIS WITH RANDOM EFFECTS. Experiments in Randomized Block Designs. Analysis of Designs with Random Factor Levels. Nested Designs. Special Designs for Process Improvement. Analysis of Nested Designs and Designs for Process Improvement. PART IV: DESIGN AND ANALYSIS WITH QUANTITATIVE PREDICTORS AND FACTORS. Linear Regression with One Predicator Variables. Linear Regression with Several Predicator Variables. Linear Regression with Factors and Covariates as Predictors. Designs and Analyses for Fitting Re sponse Surfaces. Model Assessment. Variable Selection Techniques. Appendix: Statistical Tables. Index.
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TA340 .M36 2003  Unknown 
 Edwards, Robert V. (Robert Valentino)
 New Jersey : World Scientific, c2006.
 Description
 Book — xi, 140 p. : ill. ; 24 cm.
 Summary

 Basic Statistical Concepts Measurement of Random Variables Time Series Parameter Estimation Random Sampling.
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Engineering Library (Terman)
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TA340 .E39 2006  Unknown 
 2nd ed.  New York : McGrawHill, c1998.
 Description
 Book — 1 v. (various pagings) : ill. ; 24 cm.
 Summary

 Contributors. Preface.
 Part 1: The Fundamentals.
 Part 2: Basic Statistical Methods.
 Part 3: Intermediate Methods.
 Part 4: Advanced Statistical Concepts. Appendix. Name Index. Subject Index.
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TA340 .H34 1998  Available 
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