Functional Safety analyses using an FMEDA

Failure Modes, Effects, and Diagnostic Analysis (FMEDA) is an extension of the traditional Failure Modes and Effects Analysis (FMEA), was introduced in the late 1980s by engineers at Exida to add quantitative rigor to safety analysis. While FMEA focuses on identifying potential failure modes and evaluating their impact on safety and performance, FMEDA enhances this process by incorporating numerical failure rate data and evaluating diagnostic coverage to determine how effectively failures can be detected or mitigated. By combining failure identification with reliability and diagnostic effectiveness, FMEDA enables engineers to quantitatively estimate system risk and supports compliance with functional safety standards such as IEC 61508 and ISO 26262.

Organizations often rely on specialized tools and expert-driven approaches to implement these analyses effectively

What is an FMEDA

FMEDA is a systematic, quantitative analysis technique used to evaluate how effectively a design can withstand and manage failures. It involves identifying component failure modes, their failure rates and statistical distribution based on the operational profile, including environmental conditions and applied stresses. FMEDA also evaluates the effectiveness of diagnostic and detection mechanisms in identifying failure modes, assesses the impact of latent faults, and supports predictions related to product useful life and reliability performance. It is often considered an extension of Design Failure Modes and Effects Analysis (DFMEA), enhancing traditional design-focused failure analysis by incorporating quantitative reliability and diagnostic coverage data.

Modern engineering teams increasingly use dedicated platforms to streamline FMEDA workflows and improve accuracy.

FMEA vs FMEDA (similarities and differences)

As mentioned earlier, FMEDA shares several similarities with FMEA, as it is fundamentally derived from the traditional FMEA methodology. Below is a comparison of similarities between them

	FMEA​	FMEDA​
1	Failure Mode, Effect analyses​	Failure Mode, Effect, and Diagnostic Analyses​
2	Bottom up analyses​ (Inductive analyses)	same​
3	Identifying components in the architecture, identifying failure modes, effects and mitigation mechanisms​	same​
4	Improve the overall safety and diagnostics mechanisms​	same​

Table: Similarities between FMEA and FMEDA

While FMEA and FMEDA share foundational similarities, there are important differences between the two methodologies

	FMEA​	FMEDA​
1	Failure Mode, Effect analyses​	Failure Mode, Effect, and Diagnostic Analyses​
2	Risk is calculated differently​ Risk is calculated for each failure mode​ Risk = function (severity, occurrence, and detectability)​ Risk -> Action Priority or Risk Priority Number​	Risk is calculated differently​ Risk is calculated for overall system​ PMHF – what is the total probability of failure that will lead to a safety goal violation​ SPFM – if there is a failure, what is the percentage of failures that fail safely/ multiple point​ LFM – If there is a latent fault, how good is the system to detect them (or safe by design)​
3	FMEA -> focus on individual failure modes​	FMEDA -> focus on the overall system​
4	Focus is to lower risk for each failure mode​	Focus is to improve the overall metrics -> identify the biggest contributors to risk​

Table: Differences between FMEA and FMEDA

Why perform an FMEDA ?

Figure: Benefits of FMEDA

1. Safety Compliance – Functional safety standards require a bottom-up safety analysis of the system to evaluate how component-level failures impact overall system safety. FMEDA is widely used to fulfill this requirement by systematically analyzing failure modes, their effects, and the effectiveness of diagnostic mechanisms.

2. Estimation of Failure and Reliability Metrics – While traditional FMEAs help identify component failure modes and their effects, they do not provide quantitative estimates of system failure rates or the percentage of single-point and latent failures that can be detected. FMEDA addresses this gap by incorporating failure rate data and diagnostic coverage, enabling accurate reliability and safety metric calculations. In practice, many engineering teams rely on specialized software tools to streamline these calculations and ensure accuracy.

   
   

3. Risk Prioritization and Reduction – By combining failure rate data with diagnostic effectiveness, FMEDA helps identify components that contribute most significantly to critical system failures. This allows engineers to prioritize high-risk areas and develop targeted diagnostic or mitigation strategies to reduce overall system risk.

   
   

4. Design Improvement – A primary objective of FMEDA is to drive design improvements when the risk associated with failures exceeds acceptable thresholds. This may include selecting more reliable components, enhancing diagnostic coverage, or redesigning system architecture to improve overall safety performance.

What are the applications

1. Automotive Safety – FMEDA is widely used to support compliance with ISO 26262, which requires calculation of hardware architectural metrics such as Probabilistic Metric for Hardware Failure (PMHF), Single-Point Fault Metric (SPFM), and Latent Fault Metric (LFM) to demonstrate acceptable risk levels in automotive electronic and electrical systems.

   
   

2. Robotics – FMEDA plays an important role in evaluating safety and reliability in advanced robotic systems, including humanoid and collaborative robots. It helps assess component-level failures, diagnostic effectiveness, and overall system robustness in environments where robots interact closely with humans.

   
   

3. Medical Device Safety – In safety-critical medical devices, FMEDA is used to evaluate potential hardware failures, ensure reliability of life-supporting or monitoring systems, and support compliance with applicable medical safety and risk management standards.

   
   

4. Safety Instrumented Systems (SIS) – FMEDA is commonly applied in industrial process and safety instrumented systems to verify compliance with functional safety standards such as IEC 61508 and IEC 61511, ensuring that systems designed to prevent hazardous events achieve the required Safety Integrity Levels (SILs).

Challenges while performing an FMEDA

Figure: Challenges with FMEDA

1. Resource Intensive – FMEDA requires detailed identification of components, failure modes, and associated failure rate estimation, making it a highly resource-intensive activity. Collecting field data or leveraging existing reliability databases to estimate failure rates can be time-consuming and may require significant engineering effort.

   
   

2. Difficulty in Predicting Failure Modes and Rates – Failure rate predictions are often based on historical or modeled data, which may not accurately reflect real-world operating conditions for a specific component. Reliability databases and standards such as SN 29500, IEC 61709, and FIDES provide structured methodologies for estimation, but they still represent educated approximations rather than exact predictions.

   
   

3. Dependency on Field Data – When modeled reliability data is unavailable or insufficient, organizations must rely on field data to estimate failure behavior. This requires establishing monitoring and data collection mechanisms, followed by extensive data processing and analysis, which can increase development time and complexity.

   
   

4. Limited to Known Failure Modes – FMEDA relies on identifying and analyzing known failure mechanisms. It does not inherently account for unknown or emerging failure modes, and there is limited ability to explicitly quantify uncertainty associated with unforeseen failure behaviors.

Conclusions

FMEDA provides a structured and quantitative approach to evaluating hardware reliability and safety by combining failure mode analysis with diagnostic effectiveness and failure rate modeling. Despite its challenges, it remains a critical tool for designing and validating safety-critical systems across industries where reliability and risk reduction are essential.

To effectively implement FMEDA and improve system reliability, organizations should combine the right expertise with specialized tools.