Design for Six Sigma Statistics, Chapter 5 - Assessing Measurement Systems

Overview

Main description

Here is a chapter from Design for Six Sigma Statistics, written by a Six Sigma practitioner with more than two decades of DFSS experience who provides a detailed, goal-focused roadmap. It shows you how to execute advanced mathematical procedures specifically aimed at implementing, fine-tuning, or maximizing DFSS projects to yield optimal results. For virtually every instance and situation, you are shown how to select and use appropriate mathematical methods to meet the challenges of today's engineering design for quality.

Table of contents

Part I: The Design for Six Sigma ProcessChapter 1: Developing of DFSSChapter 2: Implementing DFSSPart II: Defining Product RequirementsChapter 3: Processing the Voice of the CustomerChapter 4: Quality Function DeploymentChapter 5: Critical to Quality RequirementsChapter 6: Design for Manufacturability and AssemblyPart III: Making Decisions With DataChapter 7: Selecting Product ConceptsChapter 8: Visualizing DataChapter 9: Estimating Population ParametersChapter 10: Selecting Distribution ModelsChapter 11: Fitting Models to DataChapter 12: Tests for Changes in VariationChapter 13: Tests for Changes in AverageChapter 14: Tests for Changes in ProportionChapter 15: Making Robust DecisionsPart IV: Controlling New Product QualityChapter 16: Designing Efficient Experiments in Five MinutesChapter 17: Two-Level ExperimentsChapter 18: Robust ExperimentsPart V: Predicting New Product QualityChapter 19: Tolerance DesignChapter 20: Measures of Process CapabilityChapter 21: Tolerance Analysis for Mechanical EngineersChapter 22: Tolerance Analysis for Electrical EngineersChapter 23: DFSS ScorecardPart VI: Controlling New Product QualityChapter 24: Stabilizing ProcessesChapter 25: Measurement Systems AnalysisChapter 26: Statistical Process Control