Failure Reporting and Corrective Action Systems

Failure Reporting, Analysis, and Corrective Action Systems (FRACAS) provide the organizational framework for translating individual failure events into systematic reliability improvement. Without such systems, failure information remains scattered, root causes go unaddressed, and organizations repeatedly encounter the same problems. A well-implemented FRACAS creates a closed-loop process that captures failures, ensures thorough analysis, drives effective corrective actions, and verifies that improvements work.

This article explores the elements of effective failure reporting and corrective action systems, from database design and failure classification to corrective action tracking and effectiveness verification. Whether implementing a new FRACAS or improving an existing system, understanding these principles enables organizations to maximize the reliability improvement return from their failure analysis investments.

FRACAS Fundamentals

FRACAS is a systematic approach to managing failure information throughout its lifecycle, from initial detection through corrective action verification.

The Closed-Loop Concept

FRACAS creates a closed loop with four essential phases:

Failure Reporting: Capturing failure events with sufficient detail for subsequent analysis.
Failure Analysis: Investigating failures to determine root causes.
Corrective Action: Developing and implementing solutions to prevent recurrence.
Verification: Confirming that corrective actions effectively prevent the failure mode.

The loop closes when verification confirms effectiveness, or cycles back through analysis and corrective action if problems persist. This iterative process continues until the failure mode is eliminated or reduced to acceptable levels.

Benefits of FRACAS

Properly implemented FRACAS provides numerous benefits:

Institutional memory: Preserving failure information so lessons are not lost when personnel change.
Pattern recognition: Identifying recurring failure modes that might not be apparent from individual reports.
Resource optimization: Focusing improvement efforts on the most significant problems.
Accountability: Tracking corrective action assignments and completion.
Regulatory compliance: Meeting documentation requirements in regulated industries.
Reliability prediction: Building databases that support future reliability estimation.

FRACAS Standards

Several standards provide guidance for FRACAS implementation:

MIL-HDBK-2155: Military handbook for failure reporting and corrective action.
SAE JA1011/JA1012: Automotive reliability-centered maintenance standards with FRACAS elements.
IEC 62740: Root cause analysis guidance applicable to FRACAS.
AS9100: Quality management system requirements including corrective action processes for aerospace.

Failure Reporting

Effective corrective action depends on thorough, accurate failure reporting. The quality of downstream analysis and actions cannot exceed the quality of initial failure documentation.

Essential Failure Report Elements

A complete failure report should capture:

Identification: Unique identifier for the failure report, product serial number, part number, revision level, lot/date code.
Discovery information: When, where, and how the failure was discovered; who reported it; test or operation being performed.
Failure description: Detailed description of the symptom, observed behavior versus expected behavior, and any error codes or messages.
Environmental conditions: Temperature, humidity, vibration, or other relevant environmental factors at failure.
Operating conditions: Power supply levels, load conditions, signal inputs, and operating mode.
Operating time: Time since manufacture, installation, or last maintenance; number of cycles if applicable.
Related events: Any preceding events such as power surges, maintenance activities, or unusual operations.

Failure Report Sources

Failures may be reported from various lifecycle stages:

Design verification testing: Failures during development testing.
Manufacturing test: Failures at incoming inspection, in-circuit test, functional test, or burn-in.
Quality inspection: Visual or measurement defects found during inspection.
Field returns: Warranty claims, customer complaints, and returned units.
In-service monitoring: Automated reporting from connected products or prognostic systems.

Encouraging Thorough Reporting

Organizations must overcome barriers to failure reporting:

Simple reporting mechanisms: Make it easy to report failures with minimal administrative burden.
Non-punitive culture: Ensure reporters do not face negative consequences for reporting failures.
Feedback: Let reporters know their input led to improvements.
Training: Ensure personnel understand what information to capture and why it matters.
Standardized forms: Guide reporters to provide complete information.

Failure Classification and Coding

Consistent failure classification enables trending, pattern recognition, and meaningful statistics.

Classification Schemes

Typical classification dimensions include:

Failure mode: How the item failed (open, short, drift, intermittent, no output, etc.).
Failure mechanism: Physical or chemical process causing failure (electromigration, fatigue, corrosion, etc.).
Root cause category: Design, manufacturing, component, workmanship, handling, or use-related.
Severity: Impact on system function (critical, major, minor).
Subsystem/assembly: Location within the product architecture.
Component type: Category of failed component.

Standardized Coding Systems

Many industries have developed standard failure codes:

GIDEP failure codes: Government-Industry Data Exchange Program coding for defense and aerospace.
IEEE 1413: Standard methodology for reliability prediction and assessment.
Industry-specific schemes: Automotive, telecommunications, and medical device industries have specialized coding systems.

Custom coding schemes should be developed with consistent definitions, clear boundaries between categories, and training to ensure consistent application.

Preliminary vs. Verified Classification

Initial failure classification may be based on symptoms only. After analysis, classification should be updated to reflect verified failure mode, mechanism, and root cause. Tracking both enables assessment of initial classification accuracy and analysis effectiveness.

Failure Analysis Integration

FRACAS must integrate with failure analysis activities to translate failure reports into understood root causes.

Analysis Assignment and Tracking

The system should support:

Automatic assignment: Routing failures to appropriate analysts based on product, failure type, or workload.
Priority setting: Ensuring high-impact failures receive prompt attention.
Status tracking: Monitoring analysis progress and aging.
Workload management: Balancing analysis resources across open items.

Analysis Documentation

Analysis findings should be recorded with:

Analysis methods used: Electrical testing, visual inspection, cross-sectioning, chemical analysis, etc.
Analysis results: Data, images, and observations from each analysis step.
Root cause determination: Clear statement of the identified root cause with supporting evidence.
Confidence level: Assessment of certainty in the root cause determination.
Related failures: Links to other failures with the same or similar root causes.

When Analysis Is Not Performed

Not every failure receives full analysis. The system should document when analysis is not performed and the reason:

Recurring known issue: Failure matches a previously analyzed failure mode.
Resource constraints: Insufficient resources for analysis of low-priority items.
No fault found (NFF): Reported failure cannot be reproduced.
Sample unavailable: Failed item not available for analysis.

Corrective Action Development

Corrective actions address the root causes identified through failure analysis to prevent recurrence.

Types of Corrective Actions

Corrective actions may address different levels:

Containment actions: Immediate actions to limit damage from existing failures (rework, inspection, field service).
Corrective actions: Changes to eliminate the root cause (design changes, process changes, supplier changes).
Preventive actions: Broader improvements to prevent similar problems in other products or processes.

Effective Corrective Action Characteristics

Good corrective actions should be:

Root cause focused: Addressing the underlying cause rather than just the symptom.
Specific: Clear description of exactly what will be done.
Measurable: Defined success criteria to verify effectiveness.
Assigned: Clear ownership with accountability for completion.
Time-bound: Specific target dates for implementation.
Appropriate: Proportional to the failure impact and risk.

Corrective Action Review

Proposed corrective actions should be reviewed for:

Adequacy: Will the action actually prevent recurrence?
Feasibility: Can the action be implemented with available resources?
Side effects: Could the change introduce new problems?
Resource requirements: Cost, schedule, and personnel impact.
Verification plan: How will effectiveness be confirmed?

Implementation and Tracking

Corrective actions must be tracked from approval through implementation to closure.

Tracking Elements

The FRACAS should track:

Action status: Open, in progress, implemented, verified, closed.
Due dates: Original and current target completion dates.
Responsible party: Person or team accountable for implementation.
Progress notes: Updates on implementation progress.
Completion evidence: Documentation confirming implementation.

Escalation and Aging

Systems should include mechanisms for:

Overdue alerts: Notification when actions exceed their due dates.
Escalation paths: Automatic escalation to management for stuck or overdue items.
Aging reports: Visibility into open action backlogs and trends.

Change Control Integration

Corrective actions often require formal changes to designs, processes, or documentation. FRACAS should integrate with change control systems to:

Link to change requests: Connecting failure-driven changes to their originating failure reports.
Track change status: Updating corrective action status based on change implementation.
Verify effectivity: Confirming changes are applied to affected products.

Verification of Effectiveness

Closing the loop requires verification that corrective actions actually prevent the failure mode.

Verification Methods

Effectiveness may be verified through:

Testing: Specific tests demonstrating the failure mode no longer occurs.
Inspection: Verifying physical changes have been made correctly.
Trend monitoring: Tracking recurrence rates after implementation.
Audit: Confirming process changes are being followed.

Verification Timing

Some verification can occur immediately upon implementation; other verification requires time to observe recurrence rates. The system should support:

Implementation verification: Immediate confirmation that the change was made.
Short-term effectiveness: Early indicators that the action is working.
Long-term effectiveness: Sustained absence of recurrence over time.

Ineffective Corrective Actions

When verification shows the corrective action did not work:

Reopen the failure report: Document that the corrective action was ineffective.
Revisit root cause: Consider whether the original root cause was correct.
Develop new corrective action: Based on updated understanding.
Analyze why the action failed: Learn from ineffective actions to improve future corrective action development.

Database Design and Implementation

The FRACAS database is the repository for all failure and corrective action information.

Database Structure

Key entities typically include:

Failure reports: Core record of each failure event.
Analysis records: Findings from failure analysis activities.
Corrective actions: Individual actions with status and assignments.
Products/systems: Master data on products tracked in the system.
Components: Parts that may fail and their suppliers.
Personnel: Users, analysts, and action owners.

Relationships between entities enable linking related failures, rolling up to parent systems, and tracking all actions stemming from a single root cause.

Software Options

FRACAS implementations range from:

Spreadsheet-based: Simple but limited scalability and multi-user capability.
General-purpose databases: Custom databases built on platforms like Microsoft Access or SQL Server.
Commercial FRACAS software: Purpose-built applications with reliability engineering features.
Integrated PLM/QMS systems: FRACAS modules within broader product lifecycle or quality management systems.

Data Quality

Database value depends on data quality. Measures to ensure quality include:

Required fields: Ensuring essential information is captured.
Validation rules: Checking data consistency and format.
Controlled vocabularies: Picklists for classifications to ensure consistency.
Periodic reviews: Auditing data for completeness and accuracy.

Reporting and Analysis

FRACAS data becomes valuable through reports and analysis that reveal patterns and drive decisions.

Standard Reports

Common FRACAS reports include:

Open items summary: Failures awaiting analysis or open corrective actions.
Pareto analysis: Ranking failure modes, root causes, or affected systems by frequency.
Trend charts: Failure rates over time by product, failure mode, or root cause.
Corrective action status: Aging and completion metrics for open actions.
Effectiveness metrics: Recurrence rates before and after corrective actions.

Reliability Metrics

FRACAS data supports reliability calculations:

Failure rate: Failures per unit time or cycles.
Mean time between failures (MTBF): Average operating time between failures.
Weibull parameters: Distribution characteristics for lifetime analysis.
Reliability growth: Tracking reliability improvement over development or production.

Pattern Detection

Analysis should look for patterns indicating systemic issues:

Clustering: Failures concentrated in specific serial number ranges, time periods, or production lots.
Correlation: Relationships between failure rates and operating conditions, maintenance practices, or configuration variations.
Emerging trends: Increasing failure rates that may indicate developing problems.

Organizational Considerations

FRACAS success depends on organizational factors beyond technical implementation.

Management Commitment

Leadership support is essential for:

Resource allocation: Providing adequate personnel for reporting, analysis, and corrective action.
Priority setting: Ensuring reliability issues receive appropriate attention.
Culture creation: Establishing an environment where failure reporting is valued.
Review participation: Management engagement in FRACAS reviews.

Cross-Functional Involvement

Effective FRACAS requires participation from multiple functions:

Design engineering: Root cause analysis and design corrective actions.
Manufacturing: Process corrective actions and workmanship issues.
Quality: FRACAS administration and effectiveness monitoring.
Procurement: Supplier-related corrective actions.
Field service: Failure reporting and containment actions.

Review Boards

Regular review meetings drive accountability and progress:

Failure review boards: Evaluating new failures and assigning analysis.
Corrective action review boards: Approving proposed actions and reviewing effectiveness.
Management reviews: Higher-level review of trends and systemic issues.

Continuous Improvement of FRACAS

The FRACAS itself should be subject to continuous improvement.

Process Metrics

Track FRACAS process performance:

Reporting completeness: Are all failures being reported?
Analysis cycle time: How long does analysis take?
Corrective action closure rate: What percentage of actions close on time?
Recurrence rate: How often do closed issues recur?
Data quality metrics: Completeness and accuracy of failure reports.

Periodic Assessment

Regularly assess FRACAS effectiveness:

User feedback: Input from reporters, analysts, and action owners.
Benchmark comparison: How does the system compare to industry best practices?
Audit findings: Results from internal or external audits.
Reliability improvement: Is overall product reliability improving?

Summary

Failure Reporting, Analysis, and Corrective Action Systems transform individual failure events into systematic reliability improvement. By capturing failures comprehensively, ensuring thorough analysis, driving effective corrective actions, and verifying effectiveness, FRACAS creates a closed loop that progressively eliminates failure modes and improves product reliability.

Success requires more than just software and procedures. Organizational commitment, cross-functional involvement, and a culture that values failure reporting as a path to improvement are equally essential. When properly implemented, FRACAS becomes a powerful tool for learning from failures and preventing their recurrence.

The investment in FRACAS implementation pays dividends through reduced warranty costs, improved customer satisfaction, fewer field failures, and the institutional knowledge that enables organizations to continuously improve their products and processes.