Understanding FMEA Detection: Can You Find a Needle in a Haystack?
Failure modes and their causes can be detected in service, like tire pressure monitors on your vehicle. Is that what is assessed in the Detection column of the FMEA? This article discusses detection risk, including examples, and answers this question.
“There is nothing more deceptive than an obvious fact.”
Arthur Conan Doyle
Definition of “detection”
The Oxford English dictionary defines “detection” as “the action or process of identifying the presence of something concealed.”
What is the definition of “Detection” in an FMEA?
“Detection” is a ranking number associated with the best control from the list of detection-type controls, based on the criteria from the detection scale. The detection ranking considers the likelihood of detection of the failure mode/cause, according to defined criteria. Detection is a relative ranking within the scope of the specific FMEA and is determined without regard to the severity or likelihood of occurrence.
How is “Detection” assessed in FMEAs?
For each cause, The FMEA team assesses the detection ranking. This is the likelihood that the current detection-type controls will be able to detect the cause of the failure mode.
For Design FMEAs, detection is the ranking number corresponding to the likelihood that the current detection-type Design Controls will detect the failure mode/cause, typically in a timeframe before the product design is released for production. For Process FMEAs, detection is the ranking number corresponding to the likelihood that the current detection-type Process Controls will detect the failure mode/cause, typically in a timeframe before the part or assembly leaves the manufacturing or assembly plant.
A suggested approach is assuming the failure has occurred and then assessing the capability of the detection-type design or process control to detect the failure mode or cause. If there is no detection-type control for a given failure mode/cause, the detection ranking should be set to the highest level.
Chapter 6 of Effective FMEAs discusses an exception to this definition of detection for application in industries where the emphasis needs to be on detecting failures once the customer takes ownership (or the system is in operation).
What does a Detection Scale look like for Design FMEAs?
The following is an example of a detection scale for Design FMEAs. It is based on “Potential Failure Mode and Effects Analysis (FMEA) 4th Edition, 2008 Manual.”
What does a Detection Scale look like for Process FMEAs?
The following is an example of a detection scale for Process FMEAs. It is based on “Potential Failure Mode and Effects Analysis (FMEA) 4th Edition, 2008 Manual.”
What is an example of Detection in a Design FMEA?
[In this fictitious example, the detection ranking is assessed based on considering the criteria in the AIAG 4 scale and an estimate of a “moderately high” likelihood that the detection-type controls in the Design FMEA will detect the failure mode / cause.]
Item: Power steering pump
Function: Delivers hydraulic power for steering by transforming oil pressure at inlet ([xx] psi) into higher oil pressure at outlet [yy] psi during engine idle speed
Failure Mode: Inadequate outlet pressure (less than [yy] psi)
Effect (Local: Pump): Low pressure fluid goes to steering gear
Effect (Next level: Steering Subsystem): Increased friction at steering gear
Effect (End user): Increased steering effort with potential accident during steering maneuvers
Cause: Fluid incorrectly specified (viscosity too low)
Prevention Control: Design guidelines for hydraulic fluid selection
Detection Control: Vehicle durability testing #123
What is an example of a Detection in a Process RPN?
[In this fictitious example, the detection ranking is assessed based on considering the criteria in the AIAG 4 scale and an estimate of a “very low” likelihood that the detection-type controls in the Process FMEA will detect the failure mode / cause.]
Process Step: Induction harden shafts using induction hardening machine
Function: Induction harden shafts using induction-hardening machine ABC, with minimum hardness Brinell Hardness Number (BHN) “X”, according to specification #123.
Failure Mode: Shaft hardness less than BHN “X”
Effect (In plant): 100% scrap
Effect (End user): Shaft fractures with complete loss of performance
Effect (Assembly): Not noticeable during assembly
Severity: (Customer Effect): 8 (loss of primary function)
Severity: (Mfg/Assy Effect): 8 (major disruption)
Cause: Induction machine electrical voltage/current settings incorrect for part number
Prevention Control: Shaft hardening setup instructions
Detection Control: audit of shaft hardness
The most common misunderstanding or misapplication of the detection scale is to confuse or co-mingle the three types of detection risk:
1. Likelihood of detection by the identified controls – specifically, what is the likelihood that the current detection-type control will be able to discover the failure mode or its cause (remote, low, moderate, high, etc.)
2. Timing of the opportunity for detection – specifically, what is the timing of the current detection-type control (prior to design freeze, post design freeze, in service, etc.)
3. Type of test used to detect the cause of the problem – what is the quality of test method used to detect the failure mode or its cause (degradation test, test to failure, pass/fail test, etc.)
The detection scale must clearly identify which of the three types of detection risk is being assessed by the individual criteria of the scale.
Can you find the error in detection ranking in the example problem for next week? It is a common error, highlighted in the intermediate problem. In the advanced problem, the topic of an in-service detection scale will challenge the most experienced readers.
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In the words of Albert Einstein, “The important thing is never to stop questioning.” I invite you to ask anything at all about the broad subject of FMEAs. You may be curious about an application issue, or want another view on a challenge you are experiencing. Questions and answers are the lifeblood of learning, and we’re are all learning. I will answer all questions to the best of my ability, and promise to keep personal information confidential.Ask Carl a Question