What is FMEA Analysis?
FMEA analysis refers to the structured process of performing an FMEA. It can be performed manually through meetings with key engineering team members where the Failure Modes and Effects are detailed into a spreadsheet or similar application. A more thourough and higher integrity way to create an FMEA Analysis is through a Model-based approach, where a Digital Risk Twin is created and FMEA's are produced automatiacally through the touch of a button. Here are how FMEA Analysis are produced:
Identifying failure modes
Ways in which components, processes, or functions could fail.
Analyzing effects
Assessing the impact each failure could have on the system or customer.
Determining causes & Proritizing risk
Identifying the root causes of these failures and use metrics like Risk Priority Number (RPN) or Severity-Occurrence-Detection (S-O-D) rankings.
Mitigating failures
Recommending design or process changes to eliminate or control risks.
FMEA can be applied at various levels, including system, subsystem, and component, and is often used early in the design process, making it a vital part of modern systems engineering and risk management.
The Structure of an FMEA/FEMCA Analysis
The diagram and tables below summarizes the standard columns used in traditional FMEA (Failure Modes and Effects Analysis) and FMECA (Failure Modes, Effects, and Criticality Analysis), along with typical sources for each type of data. This structure supports engineers and analysts in understanding what information to include and where it generally originates from.
Conents & Source of Information for Each Column in the FMEA/FMECA
| Column Name | Description | Typical Source Information |
|---|---|---|
| Item/Function | The system, subsystem, or component being analyzed, along with its intended function. | System design documents, block diagrams, P&IDs, functional specifications, or bill of materials. |
| Failure Mode | The specific way in which a function or component can fail. | Historical failure data, subject matter expert input, standards (e.g., SAE J1739), and past FMEAs. |
| Failure Cause | Underlying reason for the failure mode. | Root cause analysis, design reviews, field failure reports, engineering judgment. |
| Failure Effect | The consequence of the failure mode at the local, subsystem, or system level. | Engineering analysis, system architecture documents, and impact assessments. |
| Severity (S) | Numerical ranking of how serious the effect of the failure is, often on a 1–10 scale. | Risk assessment criteria, safety requirements, engineering judgment, customer impact analysis. |
| Occurrence (O) | Estimation of how frequently the failure mode is likely to occur. | Reliability data, failure rate databases (e.g., MIL-HDBK-217), field data, expert input. |
| Detection (D) | Likelihood of detecting the failure before it impacts the system or user. | Diagnostics capabilities, testing procedures, quality control documentation, FMEA guidelines. |
| Risk Priority Number (RPN) | Calculated as Severity × Occurrence × Detection; used to rank risks. | Calculated from assigned S, O, D values. Often prioritized based on organizational thresholds. |
| Criticality Index (CI) | Used in FMECA to combine severity and probability, often incorporating mission impact. | Derived from MIL-STD-1629A or similar; based on quantitative failure data and criticality formulas. |
| Recommended Action | Proposed mitigation to eliminate or reduce the risk associated with the failure mode. | Engineering countermeasures, design improvements, process changes, or controls proposed during review meetings. |
| Responsibility & Deadline | Identifies who is accountable for implementing the action and by when. | Assigned during review meetings or project management planning. |
| Action Taken / Status | Documents whether the recommended actions have been implemented and the outcome. | Follow-up records, status updates, engineering change documentation, verification results. |
In a traditionally genrated FMECA, contents are manually compiled into spreadsheets or documents based on expert judgment, historical data, and static system descriptions, making the process time consuming and prone to inconsistencies. In contrast, a model-based FMECA, like MADE, leverages a digital system model (e.g., a Digital Risk Twin) to automatically generate and update failure modes, effects, and criticality data, ensuring traceability, consistency, and rapid iteration as the design evolves.
What are the FMEA Standards and Guidelines?
| Standard/Guidelines | Scope/Use |
|---|---|
| AIAG & VDA FMEA Handbook (2019) | Automotive industry – modern, harmonized 7-step approach integrating risk prioritization. |
| SAE J1739 | Automotive and general industry FMEA best practices; basis for many commercial templates. |
| IEC 60812 | International standard for FMEA application across sectors; includes FMECA. |
| MIL-STD-1629A | Military standard for FMECA; structured and rigorous, often used in aerospace and defense. |
| ARP5580 (SAE Aerospace) | Guidelines for applying FMEA and FMECA in aerospace systems and equipment. |
| NPR 8705.5 & NASA-HDBK-0005 | NASA-specific reliability and safety practices, including model-based FMECA guidance. |
| EN 60812 | European adoption of IEC 60812 – used in many safety-critical systems in the EU. |
| ISO 14971 | FMEA used as part of medical device risk management under this standard. |
| IEC 61508 / ISO 26262 | Functional safety standards requiring FMEA as part of hazard and risk analysis. |
Types of FMEA Analysis
Failure Modes and Effects Analysis (FMEA) is a versatile methodology tailored to assess risk across different stages of a system’s lifecycle. From early design to manufacturing and even software validation, specific types of FMEAs have evolved to address unique challenges. Understanding these variations helps organizations apply the right analysis at the right time maximizing reliability, safety, and quality.
Design FMEA (DFMEA)
USE CASES: Automotive, aerospace, electronics, and complex systems.
Focuses on identifying potential failure modes related to product design, covering components, materials, and interfaces. It is performed early in the development process to improve product robustness and reduce downstream issues.
Process FMEA (PFMEA)
USE CASES: Manufacturing engineering, quality assurance, lean production.
Assesses risks associated with manufacturing and assembly processes. It helps identify issues like incorrect machine settings, human error, or tool wear that could lead to non-conformance.
System FMEA
USE CASES: Complex platforms (e.g., aircraft, power plants, defense systems).
Analyzes failure modes across high-level system interactions and interdependencies between subsystems. It provides a broad perspective on how component-level failures can propagate through the entire system.
Software FMEA
USE CASES: Embedded systems, medical devices, autonomous systems.
Evaluates failure risks in software behavior, such as logic errors, communication faults, or unintended actions. Especially critical in systems where software failure can compromise safety.
Functional FMEA
USE CASES: MBSE workflows, safety-driven design processes.
Focuses on the intended functions of a system or component, examining how functional failures impact overall operation. It is often used in early architecture definition stages.
FMECA (FMEA + Criticality Analysis)
USE CASES: Safety-critical sectors where quantitative risk prioritization is mandated.
Extends FMEA by quantifying the severity and likelihood of failure using Criticality Index calculations. Commonly required in military and aerospace applications.
Why FMEA Matters in Today’s Engineering Environments
As engineering systems grow more complex, traditional, document based risk assessments struggle to keep up. FMEA provides a rigorous framework for identifying hidden risks—before they cause costly failures or compromise safety.
Model-based engineering environments, which utilize digital tools to simulate and analyze failure modes, are enhancing the way FMEAs are performed. These advanced platforms enable continuous validation, traceability, and automation across the lifecycle.
Traditional FMEA - Why it falls short
While conventional FMEA methods, often spreadsheet-based, can capture key insights, they have limitations:
- Manual Data Entry - introduces human error.
- Lack of Integration - with system models or real-time data.
- Static Documents - that are difficult to update and maintain.
- Limited Traceability - between design changes and risk assessments.
Why Model-Based FMEA is Better
A model-based approach to FMEA transforms it from a static exercise into a dynamic, integrated risk management tool. The Future of FMEA is Model-Based. Here’s why it’s more effective:
Digital Risk Twin Integration
Model-based tools allow FMEA to be embedded within a digital model of the system. This “Digital Risk Twin” or DRT connects functional behavior, physical architecture, and environmental conditions with failure logic, enabling:
- Automatic impact analysis across the system
- Scenario simulation and cascading failure visualization
- Faster root cause identification
Data Consistency and Reuse
By using standardized taxonomies and centralized data models, a model-based FMEA ensures consistency across safety, reliability, maintainability, and diagnostics disciplines. It also enables reuse of validated data across projects, reducing effort and error.
Title Live Synchronization with Design
Model-based platforms automatically synchronize FMEA data with system design changes. This eliminates redundant updates and maintains traceability, a crucial advantage for certification, audits, and continuous engineering.
Better Decision-Making
Integrated simulations and automated risk assessments allow engineers to evaluate design trade-offs in real time. The result? Earlier detection of critical risks and better-informed decisions that improve safety and reduce cost.
Systems are Getting More Complex - Traditional FMEA Process's Can't Cope
As systems grow in complexity and the pressure to reduce lifecycle costs increases, model-based FMEA is becoming essential. It supports proactive, integrated RAMS analysis from concept to operation, enabling digital transformation without compromising engineering rigor.
Tools like the Maintenance Aware Design Environment (MADE) are leading this shift by embedding FMEA in a broader model-based RAMS ecosystem.