Failure mode and effects analysis

Failure mode and effects analysis
Name	Failure mode and effects analysis
Abbreviation	FMEA
Type	Reliability analysis technique
First used	1940s
Developers	United States Navy, Ford Motor Company
Related	Fault tree analysis, Hazard and Operability Study, Six Sigma

Failure mode and effects analysis

Failure mode and effects analysis is a systematic technique for identifying potential failure modes within a system, assessing their effects and causes, and prioritizing mitigation actions; it is widely used across NASA, Boeing, Toyota, and General Electric programs for design robustness and safety. Originating in military and industrial practice, the method informs decision-making in contexts shaped by institutions such as the United States Department of Defense and standards-setting bodies like ISO and SAE International. Practitioners from organizations including Ford Motor Company, Allison Transmission, Lockheed Martin, and Siemens integrate FMEA with management systems guided by American Society for Quality and regulatory frameworks such as FDA oversight.

Overview

FMEA examines components, assemblies, or processes to enumerate failure modes, their causes, and consequential effects, producing documented actions that reduce risk and enhance reliability for projects by entities such as Raytheon Technologies, Northrop Grumman, Rolls-Royce, ABB Group, and Schneider Electric. The technique complements analytical approaches employed by McKinsey & Company consultants, Deloitte risk teams, and research at universities like Massachusetts Institute of Technology, Stanford University, and Imperial College London. FMEA outputs are used by program managers in European Space Agency collaborations, product engineers at Samsung Electronics, and clinical teams regulated by Centers for Medicare & Medicaid Services.

History and Development

FMEA traces roots to reliability engineering in the early 20th century with influences from Bletchley Park era systems analysis and the reliability programs at Bell Labs, later formalized by the United States Navy in naval aviation projects and adopted by Ford Motor Company during the 1950s and 1960s. The method spread through industrial networks involving Toyota Motor Corporation and Daimler AG supply chains, and standards evolution occurred through bodies like ISO and SAE International, with guidance reflected in military standards such as those from the United States Department of Defense. Academic debate and methodological refinement were advanced by research groups at Carnegie Mellon University, ETH Zurich, and University of Michigan.

Methodology and Steps

Typical FMEA workflow begins with system definition and scope established by engineering leads from firms such as Boeing or Airbus, followed by functional analysis drawing on design teams from GM and Honda. Team-based identification sessions reference failure knowledge from databases maintained by NASA and National Institute of Standards and Technology while integrating lessons from programs at Siemens and Philips. Analysts enumerate failure modes per component, determine effects on end users and downstream systems for stakeholders like Pfizer and Johnson & Johnson, trace root causes informed by maintenance data from Union Pacific Railroad and Deutsche Bahn, and propose corrective actions similar to practices at Intel Corporation and AMD. Documentation, verification, and follow-up align with compliance processes used by European Medicines Agency and auditing firms such as Ernst & Young.

Scoring and Prioritization (RPN and Alternatives)

Risk priority is commonly quantified via the Risk Priority Number (RPN) approach—multiplying Severity, Occurrence, and Detection scores—a technique used in quality programs at Toyota and Ford Motor Company; alternatives and enhancements are advocated by researchers at Princeton University and practitioners at Honeywell International. Criticisms of RPN’s multiplicative scale led to adoption of weighted ranking, action priority tables promoted by AIAG and VDA, and probabilistic methods used by NASA and European Space Agency teams. Other organizations, including Siemens, Bosch, ZF Friedrichshafen, and Continental AG, incorporate multicriteria decision analysis, fault tree analysis from MITRE Corporation collaborations, and Bayesian reliability models developed in work at Harvard University.

Applications and Industry Use

FMEA is applied to aerospace programs at NASA missions and SpaceX projects, automotive platforms at Toyota and Tesla, Inc., medical devices regulated under FDA pathways and developed by Medtronic and GE Healthcare, and process industries operated by ExxonMobil and BASF. Infrastructure projects by Bechtel and Fluor Corporation use FMEA alongside risk registers at World Bank funded initiatives, while software reliability teams at Microsoft and Google adapt the method for failure-mode thinking in cloud services used by Amazon Web Services and Oracle Corporation. FMEA supports certification efforts with Underwriters Laboratories and compliance reviews by Occupational Safety and Health Administration in industrial facilities run by Caterpillar Inc..

Limitations and Criticisms

Critics in literature from University of Cambridge, Princeton University, and Columbia University note that FMEA can produce long unprioritized lists, suffer from subjective scoring as seen in cases at Ford Motor Company and General Motors, and inadequately capture system interactions highlighted by analysts at Sandia National Laboratories and Oak Ridge National Laboratory. The RPN metric has been questioned by standards committees at ISO and researchers at Northwestern University for its mathematical shortcomings, prompting integration with formal methods from Carnegie Mellon University and probabilistic risk assessment practices used by Nuclear Regulatory Commission and Electric Power Research Institute. Practical limitations include resource demands observed at large programs like Boeing 787 development and misapplication in small firms lacking guidance from bodies such as American Society for Quality.

Category:Risk management