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Tolerance Design (paperback): A Handbook for Developing Optimal Specifications

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Tolerance Design (paperback): A Handbook for Developing Optimal Specifications


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  • Copyright 1997
  • Dimensions: 7-3/8" x 9-1/4"
  • Pages: 448
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-305234-6
  • ISBN-13: 978-0-13-305234-3

Whether an engineer, designer, drafter, or technician, each member of the design engineering team has a valuable role to play in the development of product specifications. Tolerance Design recognizes this development process as the responsibility of the entire team and provides practical solutions that each team member can readily apply. The step-by-step details of analytical and experimental tolerance development methods are clearly explained, and as a result, you will be able to develop tolerances more economically.

The book is presented in four sections: Introductory topics to position the tolerance development process, Traditional Analytical and Computer-Aided Tolerance Development, Taguchi's Approach to Experimental Methods of Tolerance Development, as well as several actual industrial case studies illustrating the book's concepts. This book includes a major emphasis for Tolerance Design using Taguchi's Quality Loss Function in harmony with Motorola's famous methods for Six Sigma quality.

The blend of practical examples with substantive case studies provides a comprehensive process approach to tolerance development. Any company interested in properly developing tolerances for their manufacturing, assembly, or service communities will find this text to be a thorough and effective training resource and reference handbook. Students of design and engineering will find this book invaluable as they prepare to enter a competitive job market where practical design optimization skills are at a premium.


Sample Content

Table of Contents


1. Introduction to Tolerancing and Tolerance Design.

The Historical Roots of Tolerancing. The State of the Art in Tolerancing Techniques. Developing Tolerances: The Role of Engineers and Designers. Concepts, Definitions, and Relationships. Matching Design Tolerances with Appropriate Manufacturing Processes. Introduction to the Taguchi Approach to Tolerance Analysis. Summary. References.

2. The Relationship of Quality Engineering and Tolerancing to Reliability Growth.

The Three Initial Phases of Product Development. The Reliability Bathtub Curve and Tolerancing. Summary. References.

3. Introductory Statistics and Data Analysis for Tolerancing and Tolerance Design.

The Role of Data in Tolerance Analysis. Graphical Methods of Data Analysis. Introduction to the Fundamentals of Descriptive Statistics. The Use of Distributions. Introduction to the Fundamentals of Inferential Statistics. Manufacturing Process Capability Metrics. Six Sigma Process Metrics. The Relationship between the Quality-Loss Function, Cp and Cpk. Summary. References.


4. Using Standard Tolerance Publications and Manufacturer's Process Capability Recommendations.

Starting the Tolerance Design Process. The Three Sigma Paradigm. Processes for Establishing Initial Tolerances. Establishing Process Capability and Process Control for Identifying Initial Tolerances. Summary. References.

5. Linear and Nonlinear Worst-Case Tolerance Analysis.

Standard Worst-Case Methods. Summary. References.

6. Linear and Nonlinear Statistical Tolerance Analysis.

The Root Sum of Squares (RSS) Approach. Motorola's Dynamic Root Sum of Squares Approach. Motorola's Static Root Sum of Squares Approach. The Nonlinear RSS Case Method. Process Diagrams for the Statistical Methods of Tolerance Stackup Analysis. The Nonlinear RSS Example. Summary. References.

7. Sensitivity Analysis and Related Topics.

The Various Approaches to Performing Sensitivity Analysis. Using Sensitivity Analysis in Concept Design. An Example of the Use of Sensitivity Analysis in Concept Development. Summary. References.

8. Computer Aided Tolerancing Techniques.

Various Software and Platform Options to Support CAT Analysis. Monte Carlo Simulations in Tolerance Analysis. Characterizing Probability Distributions for Tolerance Analysis Applications. Sensitivity Analysis Using Crystal Ball. How to Use Crystal Ball. Running the Monte Carlo Simulation. Preparing Engineering Analysis Reports. Another Computer-Aided Tolerance Approach. Summary. References.

9. Introduction to Cost-Based Optimal Tolerancing Analysis.

Skills Required for Cost-Based Optimal Tolerancing Analysis. The Various Approaches to Cost-Based Optimal Tolerancing Analysis. Summary. References.

10. Strengths and Weaknesses of the Traditional Tolerance Approaches.

Using Standard Tolerance Publications and Manufacturer's Process Capability Recommendations. Worst-Case Tolerance Analysis. The Statistical Methods of Tolerance Analysis. Sensitivity Analysis. Computer-Aided Tolerancing. Cost-Based Optimal Tolerance Analysis. How the Six Processes Relate to the Overall Product Tolerancing Process. Summary. References.


11. The Quality-Loss Function in Tolerancing and Tolerance Design.

Linking Cost and Functional Performance. An Example of the Cost of Quality. The Step Function: An Inadequate Description of Quality. The Customer Tolerance. The Quality-Loss Function: A Better Description of Quality. The Quality-Loss Coefficient. An Example of the Quality-Loss Function. Developing Quality-Loss Functions in a Customer's Environment. Constructing the Quality-Loss Economic Coefficient (A0/(D0)2). Summary. References.

12. The Application of the Quadratic Loss Function to Tolerancing.

The Difference between Customer, Design, and Manufacturing Tolerances. The Taguchi Tolerancing Equations. Relating Customer Tolerances to Engineering Tolerances. An Example of Tolerancing Using the Loss Function (Nominal-the-Best Case). Relating Customer Tolerances to Subsystem and Component Tolerances. The Linear Sensitivity Factor, b. Using the Loss Function for Multiple-Component Tolerance Analysis. An Example of Applying the Quality-Loss Function to a Multicomponent Problem. Setting Up the Problem. Identifying Critical Parameters. Converting the Traditional Tolerance Problem into a Quality-Loss Tolerance Problem. How to Evaluate Aggregated Low Level Tolerances. Using the Loss Function Nonlinear Relationships. Developing Tolerances for Deterioration Characteristics in the Design. Tolerancing the Deterioration Rate of a Higher Level Product Characteristic. Determining Initial and Deterioration Tolerances for a Product Characteristic. Summary. References.

13. General Review of Orthogonal Array Experimentation for Tolerance Design Applications.

Developing Tolerances Using a Designed Experiment. Use of Orthogonal Arrays in Tolerance Design. The Build-Test-Fix Approach. Introduction to Full Factorial Experiments. Methods to Account for Interactions within Tolerance Design Experiments. Summary. References.

14. Introducing Noise into a Tolerance Experiment.

Defining Noises and Creating Noise Diagrams and Maps. Summary. References.

15. Setting Up a Designed Experiment for Variance and Tolerance Analysis.

Preparing to Run a Statistical Variance Experiment. Using the ÷3s Transformation. A Comparison of Output Statistics. Conducting a Tolerance Experiment for Worst-Case Conditions. An L9 Experiment and Monte Carlo Simulation Using m ± 3s Levels Assuming Uniform Distributions. Metrology and Experimental Technique. Summary. References.

16. The ANOVA Method.

Accounting for Variation Using Experimental Data. A Note on Computer-Aided ANOVA. An Example of the ANOVA Process. Degrees of Freedom in ANOVA. Error Variance and Pooling. Error Variance and Replication. Error Variance and Utilizing Empty Columns. The F-Test. A WinRobust ANOVA Example. An ANOVA-TM Example. Summary. References.

17. The Tolerance Design Process: A Detailed Case Study.

The Steps for Performing the Tolerance Design Process. The ASI Circuit Case Study. Setting Up and Running the Experiment. Two-Level versus Three-Level Experiments. Techniques for Putting Noise into the Tolerance Experiment. Running the Experiment. Data Entry. Interactions in Tolerance Experiments. Analyzing the Data. Applying ANOVA. Relating the ANOVA Data to the Loss Function and Process Capability (Cp). Defining the Critica-To-Function (CTF) Factors. Defining the Cost Improvement Parameters (CIP). Identifying and Quantifying the Costs Associated with Improving Quality. Working with Suppliers to Lower Customer Losses through Reducing the Component Parameter Standard Deviations. Calculating New Variances and MSD Values Using the Variance Equation. Quantifying the Cost of Reducing the Parameter Standard Deviations. Identifying and Quantifying the Opportunities for Lowering Costs. Relaxing Tolerances and Material Specifications of CIPs to Balance Cost and Quality. New Loss and Cp after Upgrading the Critical-To-Function and Downgrading Cost Improvement Parameters. Using Tolerance Design to Help Attain Six Sigma Quality Goals. Using Tolerance Design to Improve System Reliability. Summary. References.


18. Drive System Case Studies.

The Drive System. The Drive Module. Case 1: Defining Tolerances for Standard Drive-Module Components. Case 2: Drive Module for Worst-Case Assembly Analysis. Case 3: Drive Module for RSS (Statistical) Assembly Analysis. Case 4: Drive Module for Computer-Aided Assembly Analysis. Case 5: Drive System Aided by the Use of a Designed Experiment. Summary.

Appendix A. The Z Transformation Tables and the t Transformation Table.
Appendix B. The Adjusted Z Transformation Tables.
Appendix C. The F Tables.
Appendix D. Additional References for Tolerance Design.
Appendix E: Suppliers for Tolerance Design.


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