Failure Modes and Effects Analysis (FMEA) is a systematic, proactive method for evaluating systems, processes, and risks to identify where and how they might fail and to assess the relative impact of different failures, in order to identify the parts that are most in need of change. The FMEA can be traced back to the US military standard MIL-P-1626 from the 1940s which describes Procedures for Performing a Failure Mode, Effects and Criticality Analysis (FMECA). This method of analysis was prompted by defective ammunition. Following this, in 1963 NASA developed Failure Mode and Effects Analysis (FMEA) for the Apollo mission. The succesful moon landing was in part attributed to the implementation of FEMA. When over a decade later a gas tank burst in a rear-end collision involving a Ford Pinto, the Ford Motor Company introduced FMEA. In the 1980s the German standard DIN 25 448 for failure effect analysis was given the subtitle FMEA. The German Automotive Industry Association (VDA – Verband der Automobilindustrie) further developed the method for the automotive sector and in 1986 published a description in VDA Volume 4. In 1994, the AIAG (Automotive Industry Action Group) added FMEA to the 9000 quality standard for automotive production and its suppliers. This standard then became Norm 16949 of the IATF (International Automotive Task Force), becoming the standard for OEMS worldwide. At the end of May 2019, a harmonized transatlantic FMEA standard was published by AIAG and the VDA’s Quality Management Center (QMC).
A system FMEA is the highest-level analysis of an entire system that is made up of various subsystems. Using a system FMEA you can, for example, test whether an electric motor meets all the requirements in the specifications sheet and discover and assess possible deficiencies that could lead to the requirements not being met.
DFMEA (design failure mode and effect analysis) is used when designing a new product (e.g. an electronic motor).
Using the results of Design FMEA, Process FMEA analyzes the manufacturing process of a product (e.g. production or installation of an electric motor).
- Planning and Preparation / Scoping
- Structure Analysis
- Function Analysis
- Failure Analysis
- Risk Analysis
- Optimization = Identify Measures / Define Future State
- Results Documentation
Zur Analyse potentieller Fehler, Folgen und Ursachen sollten die folgenden W-Fragen beantwortet werden:
- Which failures could occur?
- Which potential failures could occur in the identified sub-processes? (by drawing conclusions from past failures)
- What consequences would the occurrence of the failure have?
- What can cause the failures?
Each potential failure is examined to determine its potential causes.
For each identified failure/risk, the following three parameters are assessed:
- Occurence (O): How likely is it that the failure will occur?
- Severity (S): What effects will the occurrence of the failure/risk have?
- Detection (D): How likely is it that the occurrence of the failure/risk will be noticed?
The scale of this score is 1 to 10 for each parameter, so the product, the risk priority number (RPN), can take on a range of values from 1 to 1000.
To classify a risk, a risk priority number (RPN) used to be calculated.
RPN = S x O x D
The risk priority number may have a value from 1 to 1,000: 1 ≤ RPN ≤ 1,000
The higher the RPN, the more serious the error/risk and the greater the need for action.
|RPN||RISK OF FAILURE||NEED FOR ACTION||MEASURES|
|100 ≤ RPN ≤ 1,000||high||acute need for action||must be formulated and implemented|
|50 ≤ RPN ≤ 100||medium||need for action||should be formulated and implemented|
|2 ≤ RPN ≤ 50||acceptable||no urgent need for action||can be formulated and implemented|
|RPN = 1||none||no need for action||none|
However, RPN had mathematical, logical, as well as relational weaknesses. Since the release of the harmonized standard 2019, prioritization is no longer done by RPN, but by Action Priority (AP). Three classes are differentiated to determine the priority of actions: High (H), Middle (M), and Low (L). This means that risks per se are not prioritized, but the need for measures (actions) to reduce risks is assessed as high, medium or low.
- High Priority (H): the team must either identify an appropriate action to improve occurrence and/or detection or justify and document why actions taken are appropriate.
- Medium Priority (M): The team should identify appropriate action to improve the occurrence and/or detection or justify at the discretion of the organization and document why action taken is appropriate.
- Low priority (L): the team may identify actions to improve occurrence or detection.
For high and medium priority and parameter scores of 9 to 10, management should conduct a review including actions taken. This informs decision-makers in a more timely manner and allows them to take preventive action accordingly.
The parameter diagram is a block diagram that depicts the relationships between various parameters of a system. It is a simple visualization of system elements and their functions.
Block diagrams can also be used to visualize system boundaries and interfaces. This gives a good overview, as functions (and malfunctions) are realized at the interfaces to a system.
FMEA is closely related to other quality management measures and objectives. Among them are:
- CIP Continuous Improvement Process
- Genchi Genbutsu from Lean Management “Go to the place of production (Gemba) and review in reality (Genjitsu) the workers and machines in the manufacturing process (Gembutsu)”
- Evolutionary quality enhancement following plan–do–check–adjust (Shewhart/Deming cycle)
- Knowledge management
- Lessons Learned
- Idea management
Some of these disciplines can benefit from the systemic approach to production processes as set out in FMEA.