The value of a priori failure cause identification
Brainstorming, mind-mapping, and Ishikawa diagrams
Fault tree analysis history, applications, and capabilities
Relationships between logic operators and events
Fault tree gate usage and interpretation
Using inhibit functions to model probability distributions
Navigating from the failure site
Quantifying top undesired events
Failure rate sources
Using fault trees to identify redundancy-defeating failure modes
Case study
Day 2: Evaluating Potential Failure Causes
Using Failure Mode Assessment and Assignment (FMA&A) matrices
“What’s Different” analysis
Using test and inspection data, material certifications, and SPC data
Using flow charts for product performance and process evaluations
Interviewing techniques for field personnel
Customer/supplier interface issues
Engineering design and tolerance analysis
Failed hardware analysis
Evaluating failed hardware conformance
Quality Assurance compliance assessment tools
Basic metallurgical and electronic component evaluations
Component failure analysis technologies, including optical microscopy, NDT methods, SEM, Composition Analysis, FTIR, EDAX, X-ray, N-ray, SIMS, Auger and FEA
Crack appearance in different loading geometries, including axial, Bending, Torsion, Direct shear, and Contact loading
Classical microscale features, including ductile dimples, cleavage, intergranular irregularities, striations, and polymeric fractography
Commercial failure analysis laboratories
Evaluating leaks
Testing to confirm failure causes
Case study
Day 3: Design of Experiments and Systems Failure Analysis
Basic experimental design concepts
Deterministic versus statistical thinking
Hypothesis testing
The normal distribution and other basic statistical concepts
Analysis of variance
Z-tests, t-tests, and f-tests
Identifying potentially critical design and process parameters
Identifying test objectives
Test readiness reviews
Inducing failures to confirm causes
Introduction to Taguchi philosophies and Taguchi design of experiment technologies
Designing a Taguchi experiment
Selecting test parameters
Two and three level orthogonal arrays
Selecting output parameters and data collection approaches
Defining test specimen configurations
Strategies for minimizing test risk
ANOVA applied to Taguchi experiments
Multiple level experiments
Case study
Day 4: Corrective Action, Formalizing the Approach, and Course Wrap-up
Corrective action alternatives, including design modifications, process modifications, requirements relaxation, screening, and other corrective actions
Statistical Process Control as a corrective action
Corrective action order of precedence
Corrective action implementation
Corrective action scope, including work in process, inventoried material, suppliers, and delivered equipment
Evaluating corrective action efficacy
Implementing corrective actions to address other hypothesized failure causes
Using the FMA&A matrix for corrective action identification and tracking
Preventing future failures
A suggested failure analysis procedure
Creating a product-oriented Lessons Learned document
