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.

Key Takeaways (TL;DR)

What is the AIAG & VDA FMEA Handbook? The AIAG & VDA FMEA Handbook (2019) is a unified automotive standard that establishes a harmonized 1–10 rating scale for Severity (S), Occurrence (O), and Detection (D). It replaces the classic Risk Priority Number (RPN) with an Action Priority (AP) matrix to classify risks as High, Medium, or Low, prioritizing actions that prevent safety issues and regulatory non-compliances.

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.

S	Effect	Impact to Your Plant	Impact to Ship-to Plant (when known)	Impact to End User (when known)
10	High	Failure may result in health and/or safety risk for the manufacturing or assembly worker	Failure may result in health and/or safety risk for the manufacturing or assembly worker	Affects safe operation of the vehicle and/or other vehicles, the health of driver or passenger(s) or road users or pedestrians
9	High	Failure may result in in-plant regulatory noncompliance	Failure may result in in-plant regulatory noncompliance	Noncompliance with regulations
8	Moderately high	100% of production run affected may have to be scrapped	Line 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
7	Moderately high	Product may have to be sorted and a portion (less than 100%) scrapped; deviation from primary process, decreased line speed or added manpower	Line 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 noncompliance	Degradation of primary vehicle function necessary for normal driving during expected service life
6	Moderately low	100% of production run may have to be reworked off line	Line shutdown up to one hour	Loss of secondary vehicle function
5	Moderately low	A portion of the production run may have to be reworked off line and accepted	Less than 100% of product affected; strong possibility for additional defective product; sort required; no line shutdown	Degradation of secondary vehicle function
4	Low	100% of production run may have to be reworked in station before it is processed	Defective product triggers significant reaction plan; additional defective products not likely, sort not required	Very objectionable appearance, sound, vibration, harshness, or haptics
3	Low	A portion of the production run may have to be reworked in station before it is processed	Defective product triggers minor reaction plan; additional defective products not likely, sort not required	Moderately objectionable appearance, sound, vibration, harshness, or haptics
2	Low	Slight inconvenience to process, operation, or operator	Defective product triggers no reaction plan; additional defective products not likely, requires feedback to supplier	Slightly objectionable appearance, sound, vibration, harshness, or haptics
1	Very low	No discernible effect	No discernible effect or no effect	No 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).

O	Prediction of Failure Cause Occurring	Incidents per 1000 items/vehicles	Time Based Failure Cause Prediction	Type of Control	Prevention Controls
10	Extremely high	≥ 100 per thousand, ≥ 1 in 10	Every time	None	No prevention controls.
9	Very high	50 per thousand, 1 in 20	Almost every time	Behavioral	Prevention controls will have little effect in preventing failure cause.
8	Very high	20 per thousand, 1 in 50	More than once per shift	Behavioral	Prevention controls will have little effect in preventing failure cause.
7	High	10 per thousand, 1 in 100	More than once per day	Behavioral or Technical	Prevention controls somewhat effective in preventing failure cause.
6	High	2 per thousand, 1 in 500	More than once per week	Behavioral or Technical	Prevention controls somewhat effective in preventing failure cause.
5	Moderate	0.5 per thousand, 1 in 2,000	More than once per month	Behavioral or Technical	Prevention controls are effective in preventing failure cause.
4	Moderate	0.1 per thousand, 1 in 10,000	More than once per year	Behavioral or Technical	Prevention controls are effective in preventing failure cause.
3	Low	0.01 per thousand, 1 in 100,000	Once per year	Best Practices: Behavioral or Technical	Prevention controls are highly effective in preventing failure cause.
2	Very low	≤ 0.001 per thousand, 1 in 1,000,000	Less than once per year	Best Practices: Behavioral or Technical	Prevention controls are highly effective in preventing failure cause.
1	Extremely low	Failure is eliminated through prevention control	Never	Technical	Prevention 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).

D	Ability to Detect	Detection Method Maturity	Opportunity for Detection
10	Very low	No testing or inspection method has been established or is known	The failure mode will not or cannot be detected
9	Very low	It is unlikely that the testing or inspection method will detect the failure mode	The failure mode is not easily detected through random or sporadic audits.
8	Low	Test 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
7	Low	Test 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
6	Moderate	Test 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)
5	Moderate	Test 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)
4	High	System 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
3	High	System 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
2	Very high	System 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
1	Very high	Failure mode cannot be physically produced as-designed or processed	Detection 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.

Severity	Occurrence					Detection
Severity	1	2-3	4-5	6-7	8-10	Detection
1	L	L	L	L	L	1
	L	L	L	L	M	2-4
	L	L	L	L	M	5-6
	L	L	L	L	M	7-10
2-3	L	L	L	L	L	1
	L	L	L	L	M	2-4
	L	L	L	L	M	5-6
	L	L	L	L	M	7-10
4-6	L	L	L	M	M	1
	L	L	L	M	M	2-4
	L	L	L	H	H	5-6
	L	L	M	H	H	7-10
7-8	L	L	M	M	M	1
	L	L	H	H	H	2-4
	L	M	H	H	H	5-6
	L	M	H	H	H	7-10
9-10	L	L	H	H	H	1
	L	L	H	H	H	2-4
	M	M	H	H	H	5-6
	M	M	H	H	H	7-10

L - Low Risk

M - Medium Risk

H - High Risk