Root Cause Failure Analysis & Experiment Design

Day 1: Root Cause Failure Analysis and Cause Identification

• Introductory Concepts
  • Root cause failure analysis philosophy
  • The four-step problem solving approach
  • Systems and component failures
  • The inherent value of failed hardware
  • Continuous improvement concepts and root cause failure analysis
  • The value of a priori failure cause identification
  • Case Study: The Mast Mounted Sight
  • Class Discussion: Dominant Client Failures
• Identifying Potential Failure Causes
  • Brainstorming
  • Mind-mapping
  • The 5-Why’s technique
  • Ishikawa diagrams
  • Fault tree analysis history, applications, and capabilities
  • Fault tree analysis construction
  • Fault tree gate usage and interpretation
  • Fault tree analysis quantification
• Case Study: The VAMP Biomedical Device
• Group Exercises: Fault Tree Analysis Application to Client’s Failures
• Developing a Failure Analysis Action Plan
  • Using Failure Mode Assessment and Assignment (FMA&A) matrices
  • Failure analysis management
  • Failure analysis meetings
  • Failure analysis teams
• Case Study: The Coagulation Filtration Water Treatment System
• Group Exercises: Developing FMA&A Plans for Client’s Failures
• Homework Assignment: Laser Optics Debonding Case Study

Day 2: Potential Failure Cause Evaluation and Relevant Statistical Concepts

• Case Study Review
• Evaluating Potential Failure Causes
  • “What’s Different” analysis
  • Test and inspection data, material certifications, and SPC data
  • Flow charts for product performance and process evaluations
  • Failed hardware conformance assessment
  • Component failure analysis technologies, including optical microscopy, SEM, FTIR, EDAX, X-ray, N-ray, SIMS, and Auger analysis
  • Basic metallurgical and electronic component evaluations
  • Evaluating leaks
• Case Study: The CBU-87/B
• Basic Statistical Concepts and the Failure Analysis Relationship
  • The normal curve and design considerations
  • Excel evaluations for means, standard deviations, and composite standard deviations
• Group Exercises: Identifying Statistical Considerations for Client’s Failures
• The Operating Characteristic Curve
  • The Binomial distribution
  • Producer versus consumer risk
  • Using Excel to evaluate the probability of passing a test
• Group Exercises: Updating FMA&A Plans for Client’s Failures

Day 3: Statistical Evaluations, Corrective Action, Course Wrap-up

• Design of Experiments
  • Intelligent test design
  • Predicting outcomes
  • Designing meaningful experiments
  • Test readiness reviews
  • Contingency planning
• Hypothesis Testing
  • Stating the null hypothesis
  • Z-tests
  • T-tests
  • Using Excel’s built in statistics functions to simplify hypothesis testing
• Analysis of Variance
  • ANOVA history
  • The f-test
  • Using ANOVA for assessing performance differences
  • Designing tests to confirm failure causes
  • Using Excel to simplify ANOVA testing
  • ANOVA risks
• Taguchi Fractional Factorial Experiments
  • Taguchi background
  • Taguchi success stories
  • The nature of fractional factorial experiments
  • Factor selection
  • Factor limit determination
  • Calculations
  • Case Study: The Navy Aerial Refueling System
  • Class Team Exercises: Taguchi Applications Discussion for Client’s Failures
  • Using Excel to simplify Taguchi testing
• Corrective Action
  • Corrective action definitions
  • Corrective action order of precedence
  • Design modifications
  • Process modifications
  • Requirements relaxation
  • Screening
  • Other corrective actions
  • Using the FMA&A matrix for corrective action identification and tracking
  • Case Study: Corrective Action Examples
• Preventive Action
  • Using failure analysis to guide preventive action identification and implementation
  • Creating a product-oriented Lessons Learned document
  • A suggested failure analysis procedure
• Recap, Q/A, and evaluations