Statistical Tolerance

Introduction

This seminar will include a review of statistical theory and present statistical methods, which are used to better select and/or analyze Tolerance Stack-ups. The Probability (RMS) Method and tolerance optimization techniques will be discussed along with guidelines on which method(s) to use in given situations. Attendees will also view a demonstration of a excel based simulation program that analyzes the effects of form and assembly variation on the quality of a finished product.

Note: Participants should bring a scientific calculator for several in-class exercises


Objective

1. By attending in this seminar, you will be able to:

-  Apply worst case, root-mean-square, and six sigma methods for the allocation of analysis of simple-to-
   intermediate complexity tolerancing schemes

-  Use the "Risk of Misassembly" approach for tolerance allocation, and the "Main Effect" approach for
   determining dimensional variables    tolerance which exhibit the greatest impact on build variation

2. Understand and be exposed to the computer tools which can greatly  improve their statistical tolerancing
    efforts,given the intricacies of GD&T,plus-minus tolerancing and various datum schemes


Course content

1. Review of Tolerancing Methods, Tolerance Stack-Ups and the    relationship between Tolerancing and
    Quality. A High-Level Overview of Geometric Dimensioning & Tolerancing (GD&T) and Process
    Capability Measurement is Provided

2. Tolerance Synthesis (Allocation) Versus Tolerance Analysis

3. Overview of the Worst Case (non-statistical) Tolerancing Method for comparison with Statistical
    Tolerancing Results

4. Probability & Statistics Concepts Required for Statistical    Tolerancing Methods

-  Tolerance Allocation Based on "Risk of Misassembly"
-  Statistical Tolerancing Using the Root-Mean-Square (RMS) Method
-  With bilateral tolerances
-  With unilateral and/or asymmetrical tolerances
-  In 2-D and 3-D applications
-  Participant exercises

5. Analyzing Part Tolerances using Main Effect and Sensitivity Analysis Methods - Methods for Determining
   the Contribution of Process Variables to Overall Process Variation

6. Tolerance Optimization Techniques - Their Benefits in Effective Tolerancing of Parts and Assemblies

7. Introduction to Monte Carlo Analysis


Target Audience

This seminar is intended for engineers  who would like to have a good working knowledge of applying statistics to product design in order to better predict and improve product quality