AIAG VDA FMEA Tables

Severity, Occurrence, Detection & Action Priority per AIAG VDA Handbook 4th Edition (2019)

The AIAG VDA FMEA Handbook (4th Edition, 2019) is the joint automotive standard replacing the previous separate AIAG 4th Edition and VDA Volume 4. It introduces the Action Priority (AP) system — a logic-based risk categorization replacing the traditional RPN method.

AIAG VDA Severity (S) Rating Table

Severity evaluates the impact of a failure on the customer, plant, and end user. Scale: 1 (no effect) to 10 (hazardous without warning). Ratings of 9–10 always indicate critical risk.

SEffectImpact to Your PlantImpact to Ship-to Plant (when known)Impact to End User (when known)
10HighFailure may result in health and/or safety risk for the manufacturing or assembly workerFailure may result in health and/or safety risk for the manufacturing or assembly workerAffects safe operation of the vehicle and/or other vehicles, the health of driver or passenger(s) or road users or pedestrians
9HighFailure may result in in-plant regulatory noncomplianceFailure may result in in-plant regulatory noncomplianceNoncompliance with regulations
8Moderately high100% of production run affected may have to be scrappedLine shutdown greater than full production shift; stop shipment possible, field repair or replacement required (Assembly to End User) other than for regulatory noncompliance.Loss of primary vehicle function necessary for normal driving during expected service life
7Moderately highProduct may have to be sorted and a portion (less than 100%) scrapped; deviation from primary process, decreased line speed or added manpowerLine shutdown from 1 hour up to full production shift; stop shipment possible, field repair or replacement required (Assembly to End User) other than for regulatory noncomplianceDegradation of primary vehicle function necessary for normal driving during expected service life
6Moderately low100% of production run may have to be reworked off lineLine shutdown up to one hourLoss of secondary vehicle function
5Moderately lowA portion of the production run may have to be reworked off line and acceptedLess than 100% of product affected; strong possibility for additional defective product; sort required; no line shutdownDegradation of secondary vehicle function
4Low100% of production run may have to be reworked in station before it is processedDefective product triggers significant reaction plan; additional defective products not likely, sort not requiredVery objectionable appearance, sound, vibration, harshness, or haptics
3LowA portion of the production run may have to be reworked in station before it is processedDefective product triggers minor reaction plan; additional defective products not likely, sort not requiredModerately objectionable appearance, sound, vibration, harshness, or haptics
2LowSlight inconvenience to process, operation, or operatorDefective product triggers no reaction plan; additional defective products not likely, requires feedback to supplierSlightly objectionable appearance, sound, vibration, harshness, or haptics
1Very lowNo discernible effectNo discernible effect or no effectNo discernible effect

AIAG VDA Occurrence (O) Rating Table

Occurrence rates the likelihood that a failure cause will result in the failure mode. Scale: 1 (eliminated by prevention control) to 10 (failure occurs every time).

OPrediction of Failure Cause OccurringIncidents per 1000 items/vehiclesTime Based Failure Cause PredictionType of ControlPrevention Controls
10Extremely high≥ 100 per thousand, ≥ 1 in 10Every timeNoneNo prevention controls.
9Very high50 per thousand, 1 in 20Almost every timeBehavioralPrevention controls will have little effect in preventing failure cause.
8Very high20 per thousand, 1 in 50More than once per shiftBehavioralPrevention controls will have little effect in preventing failure cause.
7High10 per thousand, 1 in 100More than once per dayBehavioral or TechnicalPrevention controls somewhat effective in preventing failure cause.
6High2 per thousand, 1 in 500More than once per weekBehavioral or TechnicalPrevention controls somewhat effective in preventing failure cause.
5Moderate0.5 per thousand, 1 in 2,000More than once per monthBehavioral or TechnicalPrevention controls are effective in preventing failure cause.
4Moderate0.1 per thousand, 1 in 10,000More than once per yearBehavioral or TechnicalPrevention controls are effective in preventing failure cause.
3Low0.01 per thousand, 1 in 100,000Once per yearBest Practices: Behavioral or TechnicalPrevention controls are highly effective in preventing failure cause.
2Very low≤ 0.001 per thousand, 1 in 1,000,000Less than once per yearBest Practices: Behavioral or TechnicalPrevention controls are highly effective in preventing failure cause.
1Extremely lowFailure is eliminated through prevention controlNeverTechnicalPrevention controls are extremely effective in preventing failure cause from occurring due to design (e.g. part geometry) or process (e.g. fixture or tooling design).

AIAG VDA Detection (D) Rating Table

Detection evaluates the ability of current controls to identify a failure before it reaches the customer. Scale: 1 (certain detection) to 10 (no detection possible).

DAbility to DetectDetection Method MaturityOpportunity for Detection
10Very lowNo testing or inspection method has been established or is knownThe failure mode will not or cannot be detected
9Very lowIt is unlikely that the testing or inspection method will detect the failure modeThe failure mode is not easily detected through random or sporadic audits.
8LowTest or inspection method has not been proven to be effective and reliable (e.g. plant has little or no experience with method, gauge R&R results marginal on comparable process or this application, etc.)Human inspection (visual, tactile, audible), or use of manual gauging (attribute or variable) that should detect the failure mode or failure cause
7LowTest or inspection method has not been proven to be effective and reliable (e.g. plant has little or no experience with method, gauge R&R results marginal on comparable process or this application, etc.)Machine-based detection (automated or semi-automated with notification by light, buzzer, etc.), or use of inspection equipment such as coordinate measuring machine that should detect failure mode or failure cause
6ModerateTest or inspection method has been proven to be effective and reliable (e.g. plant has experience with method, gauge R&R results acceptable on comparable process or this application, etc.)Human inspection (visual, tactile, audible), or use of manual gauging (attribute or variable) that will detect the failure mode or failure cause (including product sample checks)
5ModerateTest or inspection method has been proven to be effective and reliable (e.g. plant has experience with method, gauge R&R results acceptable on comparable process or this application, etc.)Machine-based detection (semi-automated with notification by light, buzzer, etc.), or use of inspection equipment such as coordinate measuring machine that will detect failure mode or failure cause (including product sample checks)
4HighSystem has been proven to be effective and reliable (e.g. plant has experience with method on identical process or this application), gauge R&R results are acceptable, etc.Machine-based detection method that will detect failure mode downstream, prevent further processing or system will identify the product as discrepant and allow it to automatically move forward in the process until the designated reject unload area. Discrepant product will be controlled by a robust system that will prevent outflow of the product from the facility
3HighSystem has been proven to be effective and reliable (e.g. plant has experience with method on identical process or this application), gauge R&R results are acceptable, etc.Machine-based detection method that will detect failure mode in-station, prevent further processing or system will identify the product as discrepant and allow it to automatically move forward in the process until the designated reject unload area. Discrepant product will be controlled by a robust system that will prevent outflow of the product from the facility
2Very highSystem has been proven to be effective and reliable (e.g. plant has experience with method on identical process or this application), gauge R&R results are acceptable, etc.Machine-based detection that will detect the cause and prevent the failure mode (discrepant part) from being produced
1Very highFailure mode cannot be physically produced as-designed or processedDetection methods proven to always detect the failure mode or failure cause

AIAG VDA Action Priority (AP) Table

Action Priority replaces traditional RPN. Each failure mode is categorized as High (H), Medium (M), or Low (L) based on S, O, and D combination.

SeverityOccurrenceDetection
12-34-56-78-10
1LLLLL1
LLLLM2-4
LLLLM5-6
LLLLM7-10
2-3LLLLL1
LLLLM2-4
LLLLM5-6
LLLLM7-10
4-6LLLMM1
LLLMM2-4
LLLHH5-6
LLMHH7-10
7-8LLMMM1
LLHHH2-4
LMHHH5-6
LMHHH7-10
9-10LLHHH1
LLHHH2-4
MMHHH5-6
MMHHH7-10
L - Low Risk
M - Medium Risk
H - High Risk