FMEA

Pakistan Institute of Quality Control

FMEA is an integral part of any QS 9000 compliant quality system. Figure 1 illustrates the role of FMEA in a typical quality system.

Figure 1. The role of FMEA in a quality system.This portion of the site is intended to provide the visitor with useful and pertinent information regarding the FMEA process. It can serve as a reference document for individuals or teams familiar with FMEAs. It is not a comprehensive instruction guide for performing an FMEA, and should not be used as such.



Definitions:Cause Critical Characteristics Criticality Current Controls Customer Detection Effect Failure Mode FMEA Element

• Function • Occurrence • Risk Priority Number

• Severity • Significant Characteristics

• Special Process Characteristics

• Special Product Characteristics

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Cause

A Cause is the means by which a particular element of the design or process results in a Failure Mode.


Critical Characteristics:

Critical Characteristics are Special Characteristics defined by Ford Motor Company that affect customer safety and/or could result in non-compliance with government regulations and thus require special controls to ensure 100% compliance.


Criticality:

The Criticality rating is the mathematical product of the Severity and Occurrence ratings. Criticality = (S) × (O). This number is used to place priority on items that require additional quality planning.


Current Controls:

Current Controls (design and process) are the mechanisms that prevent the Cause of the Failure Mode from occurring, or which detect the failure before it reaches the Customer.


Customer:

Customers are internal and external departments, people, and processes that will be adversely affected by product failure.


Detection:

Detection is an assessment of the likelihood that the Current Controls (design and process) will detect the Cause of the Failure Mode or the Failure Mode itself, thus preventing it from reaching the Customer.


Effect:

An Effect is an adverse consequence that the Customer might experience. The Customer could be the next operation, subsequent operations, or the end user.


Failure Mode:

Failure Modes are sometimes described as categories of failure. A potential Failure Mode describes the way in which a product or process could fail to perform its desired function (design intent or performance requirements) as described by the needs, wants, and expectations of the internal and external Customers.


FMEA Element:

FMEA elements are identified or analyzed in the FMEA process. Common examples are Functions, Failure Modes, Causes, Effects, Controls, and Actions. FMEA elements appear as column headings in the output form.


Function:

A Function could be any intended purpose of a product or process. FMEA functions are best described in verb-noun format with engineering specifications.


Occurrence:

Occurrence is an assessment of the likelihood that a particular Cause will happen and result in the Failure Mode during the intended life and use of the product.


Risk Priority Number:

The Risk Priority Number is a mathematical product of the numerical Severity, Occurrence, and Detection ratings. RPN = (S) × (O) × (D). This number is used to place priority on items than require additional quality planning.


Severity:

Severity is an assessment of how serious the Effect of the potential Failure Mode is on the Customer.


Significant Characteristics:

Significant Characteristics are Special Characteristics defined by Ford Motor Company as characteristics that significantly affect customer satisfaction and require quality planning to ensure acceptable levels of capability.


Special Process Characteristics:

Special Process Characteristics are process characteristics for which variation must be controlled to some target value to ensure that variation in a Special Product Characteristic is maintained to its target value during manufacturing and assembly.


Special Product Characteristics:

Special Product Characteristics are product characteristics for which reasonably anticipated variation could significantly affect a product’s safety or compliance with governmental standards or regulations, or is likely to significantly affect customer satisfaction with a product.


Acronyms:

8-D Eight Disciplines of Problem Solving

AIAG Automotive Industry Action Group

APQP Advanced Product Quality Planning

ASQC American Society for Quality Control

DOE Design of Experiments

FMEA Potential Failure Mode and Effects Analysis

FTA Fault Tree Analysis

ISO International Organization for Standardization

QFD Quality Function Deployment

QOS Quality Operating System

RFTA Reverse Fault Tree Analysis

RPN Risk Priority Number

SPC Statistical Process Control


The FMEA discipline was developed in the United States Military. Military Procedure MIL-P-1629, titled Procedures for Performing a Failure Mode, Effects and Criticality Analysis, is dated November 9, 1949. It was used as a reliability evaluation technique to determine the effect of system and equipment failures. Failures were classified according to their impact on mission success and personnel/equipment safety. The term "personnel/equipment", taken directly from an abstract of Military Standard MIL-STD-1629, is notable. The concept that personnel and equipment are interchangeable does not apply in the modern manufacturing context of producing consumer goods. The manufacturers of consumer products established a new set of priorities, including customer satisfaction and safety. As a result, the risk assessment tools of the FMEA became partially outdated. They have not been adequately updated since.


In 1988, the International Organization for Standardization issued the ISO 9000 series of business management standards. The requirements of ISO 9000 pushed organizations to develop formalized Quality Management Systems that ideally are focused on the needs, wants, and expectations of customers. QS 9000 is the automotive analogy to ISO 9000. A Task Force representing Chrysler Corporation, Ford Motor Company, and General Motors Corporation developed QS 9000 in an effort to standardize supplier quality systems. In accordance with QS 9000 standards, compliant automotive suppliers shall utilize Advanced Product Quality Planning (APQP), including design and process FMEAs, and develop a Control Plan.

http://www.iso.ch/iso/en/ISOOnline.frontpage

http://qs9000.asq.org/


Advanced Product Quality Planning standards provide a structured method of defining and establishing the steps necessary to assure that a product satisfies the customer’s requirements. Control Plans aid in manufacturing quality products according to customer requirements in conjunction with QS 9000. An emphasis is placed on minimizing process and product variation. A Control Plan provides "a structured approach for the design, selection, and implementation of value-added control methods for the total system." QS 9000 compliant automotive suppliers must utilize Failure Mode and Effects Analysis (FMEA) in the Advanced Quality Planning process and in the development of their Control Plans.


The Automotive Industry Action Group (AIAG) and the American Society for Quality Control (ASQC) copyrighted industry-wide FMEA standards in February of 1993, the technical equivalent of the Society of Automotive Engineers procedure SAE J-1739. The standards are presented in an FMEA Manual approved and supported by all three automakers. It provides general guidelines for preparing an FMEA.

This site is dedicated to overcoming some deficiencies of the Potential Failure Mode and Effects Analysis (FMEA), as it is currently being deployed in the U.S. automotive industry. An FMEA is commonly defined as "a systematic process for identifying potential design and process failures before they occur, with the intent to eliminate them or minimize the risk associated with them."

http://www.aiag.org/

http://www.asq.org/

http://www.sae.org/servlets/productDetail?PROD_TYP=STD&PROD_CD=J1739_200208


In the progression of time, a Failure Mode comes between a Cause and an Effect. One of the most confusing issues for new practitioners of FMEA is that any Cause that itself has a Cause might be a Failure Mode. Any Effect that itself has an Effect might also be a Failure Mode. In different contexts, a single event may be a Cause, an Effect, and a Failure Mode. Consider for example Figure 2, a series of events that could occur during the life of a disposable penlight.



In an analysis of the exterior casing of a penlight, "Allows excess moisture" would be a Failure Mode. One of the intended functions of the penlight case is to protect the internal components from excess moisture during normal operation. A failure to prevent moisture during normal operation is a Failure Mode since protective casings and other design features are intended to prevent moisture. Causes appear above the Failure Mode in Figure 2. Effects appear below.

In the analysis of the penlight bulb, a different Function and Failure Mode(s) must be considered. The penlight bulb is intended to provide light of specific intensity when the device is activated during its expected lifetime. This is one of its Functions, or intended purposes. A dim bulb is a failure to provide the specified intensity of light and is therefore a Failure Mode of the penlight bulb. This example illustrates that Causes, Effects, and Failure Modes can change depending on the Function being analyzed. Functions change depending on the object of the analysis, either product or process. Therefore, an early, important step in an FMEA is to clearly define the scope: the component, system, or process that is to be analyzed.


Most real-world systems do not follow the simple Cause-Effect model. A single Cause may have multiple Effects. A combination of Causes may lead to an Effect, or they may lead to multiple Effects. Causes can themselves have Causes, and Effects can have subsequent downstream Effects. The Failure Mode must also be considered in all of these models. Figure 3 illustrates the relationship between a Function, a Failure Mode, Potential Causes, and Effects. In the FMEA model presented in this document, Causes do not automatically result in the Failure Mode. The term ‘Potential’ is used to describe Causes, to indicate this uncertainty. The model also assumes that all Effects will result given that the Failure Mode has occurred. Therefore, ‘Potential’ is not used to describe Effects.


Figure 3. FMEA RelationshipsIn Figure 3, A pentagon is used to represent the

Failure Mode for two reasons. First, Failure Modes can be grouped into one of five categories of failure. Secondly, the asymmetrical pentagon is mirrored to indicate that Failure Modes can also be described as anti-Functions.


FMEA Elements are the building blocks of related information that comprise an analysis. The team approach is almost essential in identifying FMEA elements. Although actual document preparation is often the responsibility of an individual, FMEA input should come from a multi-disciplinary team. The team should consist of knowledgeable individuals with expertise in design, manufacturing, assembly, service, quality, and reliability. The responsible engineer typically leads the FMEA team. Members and leadership may vary as the system, product, and process designs mature.


Once the object of the analysis has been established, the next step in the FMEA process is to identify Functions. A Function is an intended purpose of the product or process being analyzed. If a system is being considered, Functions of individual subsystems should also be identified. Potential Failure Modes, or categories of failure, can then be identified by describing the way in which the object fails. Failure Modes fall into 1 of 5 possible failure categories:

complete failure.

partial failure.

intermittent failure.

failure over time.

over-performance of Function.


In the penlight example, suppose "Provide Light at 3 ± .5 candela" is defined as a Function. The following Failure Modes could be identified:

no light.

dim light.

erratic blinking light.

gradual dimming of light.

too bright.


The purpose of these five Failure Mode groupings is to assist the FMEA team identify all possible Failure Modes. Looking for Failure Modes in these groupings may reveal some unusual failure possibilities that otherwise would not have been considered. Poorly defined Functions may also be revealed. In this example, a light that does not turn off (over-performs its Function) is a product failure, even though the Function "Provide light at 3 ± .5 candela" does not fail. This implies the need for an additional Function, such as "Default to off when not in use", which may have been overlooked when Functions were originally identified. The original Function is rephrased as: "Provides light at 3 ± .5 candela when on." A partial, intermittent, gradual or over-performance type failure of one Function may be a complete failure of another unidentified Function. Use of the Failure Mode categories can help reveal these Functions.


After Functions and Failure Modes have been established, the next step in the FMEA process is to identify potential downstream consequences when the Failure Mode occurs. This should be a team brainstorming activity. After consequences have been identified, they must be fit into the FMEA model as Effects. In the FMEA model presented by the Haviland Consulting Group, it is assumed that Failure Mode Effects always occur when the Failure Mode occurs; there is no representation for the likelihood that a Failure Mode will result in an Effect. The Procedure for Potential Consequences is applied to account for unlikely or remote consequences. The Procedure explicitly associates Effects with the circumstances under which they occur through the identification of additional Failure Modes.


The Procedure for Potential Consequences:

• Begin with a Failure Mode (referred to as FM-1), and a list of all its potential consequences.

•

Separate the consequences that can be assumed to result whenever the Failure Mode FM-1 occurs. Identify these as Effects of FM-1.

•

Write additional Failure Modes for the remaining consequences (consequences which could result when FM-1 occurs, depending on the circumstances under which FM-1 occurred).

The new Failure Modes imply that unlikely consequences will result by including the circumstances under which they occur.

• Separate the consequences that can be assumed to result whenever the additional Failure Modes and their special circumstances occur. Identify these consequences as Effects of the additional Failure Modes.


Consider this example, which illustrates the Procedure for Potential Consequences. During the Effects brainstorm, the team may tend to identify very severe consequences and the unlikely circumstances under which they occur. When analyzing the penlight bulb, a team member may observe that the bulb could prematurely burn out when being used as a flashlight, the resulting darkness causing the user to trip, fall, and be injured. Another member may observe that atmospheric pressure variation could cause the bulb to explode while being used for an eye examination, resulting in injury. Such extraneous predicaments are typical of a brainstorm and can be expected. But rather than write a new Failure Mode for every bizarre situation recorded by the team, the events should be grouped into a broad Effect category, such as "injury or death". Ultimately, Effects are categorized into one of ten groups, according to Severity. It is advantageous to write Failure Modes that encompass all the Effects in a Severity grouping, such as "Fails to provide 3 ± .5 candela of light under critical conditions". All product failures that lead to injury or death are automatically included; there is no need to attempt to identify all the circumstances under which injury or death could result. The tradeoff for this convenience is that the likelihood of failure under any critical situation must be factored into the Occurrence rating.


The first step in analyzing risk is to quantify the Severity of the Effects. Effects are rated on a scale of 1 to 10, 10 being the most severe. The team should agree on consistent evaluation criteria and a sensible ranking system. The design and process ranking systems presented in Table 1 and Table 2 are based on AIAG standards. Effects are evaluated as a group when assessing risk, even though they are assigned Severity values individually. It is assumed that all Effects will result if the Failure Mode occurs. Therefore, the most serious Effect takes precedence when evaluating risk potential. This model accounts for Causes that have multiple Effects. Issuing design and process changes can reduce Severity ratings.Notes of interest:

http://www.fmeca.com/ffmethod/tables/dfmea.htm

http://www.fmeca.com/ffmethod/tables/pfmea.htm


The scales do not discriminate between failures that results in catastrophic death, minor injury, or government regulation violation. A defect noticed by most customers is less than halfway up the Severity scale. "No effect" has a ranking of 1. There is no zero. Note: These tables differ slightly from those published by the AIAG. Specific references to motor vehicles have been removed. The tables are similar to AIAG tables in that they are suggested ranking systems. Because these tables are suggested, the actual criteria used to prioritize risk should be documented with the FMEA.


EffectCriteria: Severity of Effect for DFMEA

Hazardous –no warning

Failure affects safe product operation or involves noncompliance with government regulation without warning.

Hazardous – with warning

Failure affects safe product operation or involves noncompliance with government regulation with warning.

Very High Product is inoperable with loss of primary Function.

High Product is operable, but at reduced level of performance.

Moderate Product is operable, but comfort or convenience item(s) are inoperable.


LowProduct is operable, but comfort or convenience item(s) operate at a reduced level of performance.

Very LowFit & finish or squeak & rattle item does not conform. Most customers notice defect.

MinorFit & finish or squeak & rattle item does not conform. Average customers notice defect.

Very MinorFit & finish or squeak & rattle item does not conform. Discriminating customers notice defect.

None No effect

Table 1.

Suggested evaluation criteria and ranking system for the Severity of Effects for a design FMEA


EffectCriteria: Severity of Effect for PFMEA

Rank

Hazardous – no warning

May endanger machine operator or assembly operator. Failure affects safe product operation or noncompliance with government regulation. Failure will occur without warning.

10

Hazardous – with warning

May endanger machine operator or assembly operator. Failure affects safe product operation or noncompliance with government regulation. Failure will occur with warning.

9

Very HighMajor disruption to production line. 100% of product may have to be scrapped. The product is inoperable with loss of primary Function.

8

HighMinor disruption to production line. Product may have to be sorted and a portion scrapped. The product is operable, but at a reduced level of performance.

7

ModerateMinor disruption to production line. A portion of the product may have to be scrapped (no sorting). Product is operable, but some comfort / convenience item(s) are inoperable

6


Very LowMinor disruption to production line. Product may have to be sorted and a portion reworked. Fit & finish or squeak & rattle item does not conform. Most Customers notice the defect.

4

MinorMinor disruption to production line. A portion of the product may have to be reworked on-line but out-of-station. Fit & finish or squeak & rattle item does not conform. Average customers notice the defect.

3

Very Minor

Minor disruption to production line. A portion of the product may have to be reworked on-line but in-station. Fit & finish or squeak & rattle item does not conform. Discriminating customers notice the defect.

2

None The Failure Mode has no Effect. 1

LowMinor disruption to production line. 100% of the product may have to be reworked. Product is operable, but some comfort / convenience items operate at a reduced level of performance.

5

Table 2. Suggested evaluation criteria and ranking system for the Severity of Effects in a process FMEA


After Effects and Severity have been addressed, the next step is to identify Causes of Failure Modes. This is another team activity. Identification should start with Failure Modes that have the most severe Effects. In a design FMEA, design deficiencies that result in a Failure Mode are Causes of failure. Design deficiencies that induce a manufacturing or assembly error are also included in design FMEAs as Causes. The design FMEA assumes that manufacturing and assembly specifications are met, and only seeks to identify failures resulting from product design.

In a process FMEA, Causes are specific errors described in terms of something that can be corrected or controlled. The process FMEA assumes that the product is adequately engineered, and will not fail because of a design deficiency. This does not imply that all inputs to the process meet engineering specifications. Variation in purchased parts and material used in the process should be considered in the process FMEA.


Causes are rated in terms of Occurrence. Occurrence is the likelihood that that a particular Cause will occur and result in the Failure Mode during the intended life and use of the product. This definition is distinctly different from the definition published by the AIAG. In the AIAG FMEA model, Occurrence is simply the likelihood that a Cause or mechanism of failure will occur. It is assumed that the failure itself could occur, but not necessarily. Since Occurrence is defined only as the likelihood the Cause will occur, there is no way of quantifying the likelihood that the Failure Mode and subsequent Effects will result. The Occurrence definition preferred by The Haviland Consulting Group, used in combination with the Procedure for Potential Consequences, accounts for the fact that Causes do not always lead to Failure Modes and subsequent Effects. When applicable, the Procedure for Potential Consequences isolates severe Effects from the group by definition of a new Failure Mode with special circumstances. The Causes of the new Failure Mode are assigned Occurrence values. The new Occurrence values represent the remote likelihood that the customer will experience the Effect. In the AIAG model, there is no risk-prioritizing advantage to writing additional Failure Modes because Causes and Failure Modes are not necessarily linked by Occurrence.

http://www.fmeca.com/ffmethod/elem/effects.htm#The Procedure for Potential Consequences:


The Ford Motor Company has added a Cause-Failure Mode condition to the AIAG model, stating that if the Cause occurs, the Failure Mode always results. This condition effectively links Occurrence with Failure Modes, but Failure Mode-Effect causality in the Ford model is not mentioned in their FMEA handbook. If the Ford model assumes that Effects do not always occur when the Failure Mode occurs, then Occurrence has no real bearing on whether the customer will experience the Effect. If the Ford model assumes that Effects always occur when the Failure Mode occurs, then the FMEA team is forced to assume that a Cause will automatically lead to every possible Effect. This is generally untrue, leading to overestimated risk. In the FMEA model presented in this thesis, the Procedure for Potential Consequences and a new Occurrence definition are used to handle this Cause-Failure Mode-Effect causality problem. The Ford and AIAG models do not include the Procedure for Potential Consequences, or a similar solution.

Unlike Effects, Causes are not evaluated as a group when assessing risk. Separate values are assigned to each Cause of the Failure Mode. Current Controls sometimes prevent the Cause of failure, the Failure Mode itself, or its Effects. Such Controls, designated Type (1), are most desirable and can reduce initial Occurrence ratings.


Table 3 and Table 4 are based on AIAG standards. Most failure rates will fall between two numbers on the scale. The standard practice is to round to the higher of the two Occurrence values. For example, a failure that occurs every 14,000 parts would be assigned an Occurrence value of 4, even though 1/14000 is closer to 1/15000 (Occurrence = 3) than it is to 1/2000 (Occurrence =

4). For cases where the failure rates are completely unknown, assume that Occurrence = 10. Occurrence ratings can be based information from similar products and process when available.

http://www.fmeca.com/ffmethod/tables/dfmea1.htm

http://www.fmeca.com/ffmethod/tables/pfmea1.htm


Notes of Interest:

•The probabilities represent the likelihood that the Cause will occur and result in the Failure Mode, not just the chances that it will occur. •The scales are not linear. •An Occurrence of 10 does not discriminate between failures that occur over half the time and failures that occur every time. •An Occurrence of 1 does not discriminate between remote and zero chance of failure.

Note: These tables differ slightly from those published by the AIAG. Specific references to motor vehicles have been removed. The tables are similar to AIAG tables in that they are suggested ranking systems. Because these tables are suggested, the actual criteria used to prioritize risk should be documented with the FMEA.


Probability of Failure Failure RatesR

ank

Very High: Failure is almost inevitable≥ 1 in 2 10

1 in 3 9

High: Repeated failures1 in 8 8

1 in 20 7

Moderate: Occasional failures

1 in 80 6

1 in 400 5

1 in 2000 4

Low: Relatively few failures1 in 15,000 3

1 in 150,000 2

Remote: Failure is unlikely ≤ 1 in 1,500,000 1

Table 3.

Suggested evaluation criteria and ranking system for the Occurrence of Failure in a design FMEA


Probability of Failure Failure Rates CpkR

ank

Very High: Failure is almost inevitable≥ 1 in 2 < 0.33 10

1 in 3 ≥ 0.33 9

High: Generally associated with processes similar to previous processes that have often failed

1 in 8 ≥ 0.51 8

1 in 20 ≥ 0.67 7

Moderate: Generally associated with processes similar to pervious processes which have experienced occasional failures, but not in major proportions

1 in 80 ≥ 0.83 6

1 in 400 ≥ 1.00 5

1 in 2000 ≥ 1.17 4

Low: Isolated failures associated with similar processes

1 in 15,000 ≥ 1.33 3

Very Low: Only isolated failures associated with almost identical processes

1 in 150,000 ≥ 1.50 2

Remote: Failure is unlikely. No failures ever associated with almost identical processes

≤ 1 in 1,500,000 ≥ 1.67 1

Table 4.

Suggested evaluation criteria and ranking system for the Occurrence of Failure in a Process FMEA


Current Control

Design and Process controls are grouped according to their purpose.

Type (1): These controls prevent the Cause or Failure Mode from occurring, or reduce their rate of occurrence.

Type (2):

These controls detect the Cause of the Failure Mode and lead to corrective action.

Type (3):

These Controls detect the Failure Mode before the product reaches the customer. The customer could be the next operation, subsequent operations, or the end user.

The distinction between controls that prevent failure (Type 1) and controls that detect failure (Types 2 and 3) is important. Type 1 controls reduce the likelihood that a Cause or Failure Mode will occur, and therefore affect Occurrence ratings. Type 2 and Type 3 Controls detect Causes and Failure Modes respectively, and therefore affect Detection ratings.

http://www.fmeca.com/ffmethod/elem/detectio.htm


Detection values are associated with Current Controls. Detection is a measurement of the ability of Type (2) Controls to detect Causes or mechanisms of failure, or the ability of Type (3) Controls to detect subsequent Failure Modes. One Detection value is assigned to the system of Current Controls, which represents a collective ability to detect Causes or Failure Modes. Controls can be grouped and treated as a system when they operate independently, as each individual Control increases overall detection capabilities. The design and process ranking systems presented in Table 5 and Table 6 are based on AIAG standards.

Notes of Interest:

•High values indicate a lack of detection ability.

•The tables are not quantitative; relative terms are used.

•The adjectives used to describe the likelihood of Detection indicate a generally linear relationship.

•A Detection value of 1 does not imply 100% detection.

Note: These tables differ slightly from those published by the AIAG. Specific references to motor vehicles have been removed. The tables are similar to AIAG tables in that they are suggested ranking systems. Because these tables are suggested, the actual criteria used to prioritize risk should be documented with the FMEA.

http://www.fmeca.com/ffmethod/elem/current.htm

http://www.fmeca.com/ffmethod/elem/current.htm

http://www.fmeca.com/ffmethod/tables/dfmea2.htm

http://www.fmeca.com/ffmethod/tables/pfmea2.htm


Detection Criteria: Likelihood of Detection by Design ControlR

ankAbsolute Uncertainty

Design Control does not detect a potential Cause of failure or subsequent Failure Mode; or there is no Design Control

10

Very Remote

Very remote chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

9

RemoteRemote chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

8

Very LowVery low chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

7

LowLow chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

6

ModerateModerate chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

5

Moderately High

Moderately high chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

4

HighHigh chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

3

Very HighVery high chance the Design Control will detect a potential Cause of failure or subsequent Failure Mode

2

Almost Certain

Design Control will almost certainly detect a potential Cause of failure or subsequent Failure Mode

1

Table 5. Suggested evaluation criteria and ranking system for the Detection of a Cause of failure or Failure Mode in a design FMEA.


Detection Criteria: Likelihood of Detection by Process ControlR

ankAlmost Impossible

No known Controls available to detect Failure Mode or Cause 10

Very RemoteVery remote likelihood current Controls with detect Failure Mode or Cause

9

Remote Remote likelihood current Controls with detect Failure Mode or Cause 8

Very Low Very low likelihood current Controls with detect Failure Mode or Cause 7

Low Low likelihood current Controls with detect Failure Mode or Cause 6

Moderate Moderate likelihood current Controls with detect Failure Mode or Cause 5

Moderately High

Moderately high likelihood current Controls with detect Failure Mode or Cause

4

High High likelihood current Controls with detect Failure Mode or Cause 3

Very High Very high likelihood current Controls with detect Failure Mode or Cause 2

Almost Certain

Current Controls almost certain to Failure Mode or Cause. Reliable detection controls are known with similar processes.

1

Table 6. Suggested evaluation criteria and ranking system for the Detection of a Cause of failure or Failure Mode in a process FMEA


A tabular FMEA documentation form has been standardized by the AIAG. All input data must be organized on the output form in the spaces and columns provided. Some companies compile FMEA data on worksheets, and then transfer the information to the form. Other companies with electronic versions of the form can fill in the table as FMEA elements are identified. FMEA Facilitator collects the input data through an organized and intuitive interface and places it on the form automatically.


The fundamental purpose of the FMEA is to recommend and take actions that reduce risk. Actions taken often result in a lower Severity, Occurrence, or Detection rating. Adding validation or verification controls can reduce Detection. Design or process revision may result in lower Severity and Occurrence ratings. The revised ratings are documented with the originals on the tabular FMEA form. If no action is recommended, the decision not to act should also be noted. Effective follow-up programs are also necessary, as the purpose of the FMEA is defeated if any recommended actions are left undressed.


The Risk Priority Number (RPN) is a mathematical product of the seriousness of a group of Effects (Severity), the likelihood that a Cause will create the failure associated with those Effects (Occurrence), and an ability to detect the failure before it gets to the customer (Detection). In equation form, RPN = S • O • D. This number is used to help identify the most serious risks, leading to corrective action. Inspection of the equation reveals that the RPN method for assessing risk is an oversimplification. Severity, Occurrence, and Detection are not equally weighted with respect to one another in terms of risk. The distortion is compounded by the non-linear nature of the individual ranking scales. As a result, some S-O-D scenarios produce RPNs that are lower than other combinations, but more risky. Furthermore, the RPN scale itself has some non-intuitive statistical properties. The initial and correct observation that the scale starts at 1 and ends at 1000 often leads to incorrect assumptions about the middle of the scale. Table 7 contains some common faulty assumptions.


Table 7. RPN Scale Statistical Data

Incorrect Assumption Actual Statistical Data

The average of all RPN values is roughly 500.

Roughly 50% of RPN values are above 500. (The median is near 500.)

The Average RPN value is 166.

6% of all RPN values are above 500. (The median is 105.)

There are 1000 possible RPN values. There are 120 unique RPN values.


The 1000 RPN numbers generated from all possible combinations of Severity, Occurrence, and Detection are plotted on this histogram. High Severity values merit special attention, particularly when coupled with high Occurrence values. The term Criticality was developed to call attention to these combinations. Criticality is defined as the mathematical product of Severity and Occurrence. This definition does not fully correct the problem. Severity and Occurrence are still unequal in terms of risk, and their ranking scales are still non-linear. The contour plot of Figure 4 compares Criticality with an expert risk assessment of the actual S-O combination, with 5 chosen as an arbitrary Detection value. Deep blue signifies a strong correlation between Criticality and risk, while red indicates a large discrepancy.The discrepancy between RPN and expert risk assessment of the 1000 S-O-D combinations is even more prominent. Despite the shortcomings of RPN and Criticality, they are used and misused regularly for risk assessment.

http://www.fmeca.com/ffmethod/elem/rpn.htm

http://www.fmeca.com/ffmethod/elem/critical.htm



Figure 4. Criticality and Risk Discrepancy Contour Plot This contour plot represents the estimated discrepancy between Criticality and actual risk for a system with average failure detecting controls (Detection = 5). Notice the dramatic discrepancy at [Severity = 10, Occurrence = 2]. In this situation, a failure with potentially catastrophic consequences is expected to occur (eventually), and can therefore also pose great risk. Based on the Criticality scale, this situation is assigned a value of 20 (out of a possible maximum of 100), and may consequently be overlooked.


The AIAG defines a Special Product Characteristic as a product characteristic for which reasonably anticipated variation could significantly affect a product’s safety or compliance with governmental standards or regulations, or is likely to significantly affect customer satisfaction with a product. Ford Motor Company divides Special Characteristics into two categories: Critical Characteristics and Significant CharacteristicsCritical Characteristics are defined by Ford as product or process requirements that affect compliance with government regulation or safe product function, and which require special actions or controls. In a design FMEA, they are considered Potential Critical Characteristics. A Potential Critical Characteristic exists for any Severity rating greater than or equal to 9. In the process FMEA, they are referred to as Actual Critical Characteristics. Any characteristic with a Severity of 9 or 10 which requires a special control to ensure detection is a Critical Characteristic. Examples of product or process requirements that could be Critical Characteristics include dimensions, specifications, tests, assembly sequences, tooling, joints, torques, welds, attachments, and component usages. Special actions or controls necessary to meet these requirements may involve manufacturing, assembly, a supplier, shipping, monitoring, or inspection. Significant Characteristics require special controls because they are important to customer satisfaction. Severity ratings between 5 and 8 coupled with an Occurrence rating greater than 3 indicate Significant Characteristics. In a design FMEA, they are Potential Significant Characteristics. In the process FMEA, if a special control is required to ensure detection then an Actual Significant Characteristic exists.Companies have not standardized a method for grouping and denoting Special Product Characteristics. Nomenclature and notation will vary.




Contents

What is Control Plan? Why Control Plan? Process without Control plan…. exampleLinkage between flow charts, process FMEA,

control plans, Proc. Doc. and other documentsDescription and usage of Columns of Control

PlanChanging Control PlanExpectationsPractice session


The Control Plan describes the actions that are required at each phase of the process to ensure that all process outputs will be in state of control

Control plan is a living document, reflecting the current methods of control, and measurement systems used

Accessible at work station

APQP Manual definition…

What is Control Plan ?


Communicates what do we have to check and control throughout the process

Helps new people to understand the process and its control steps

Control plan is needed to document and communicate the process & Product parameters, process controls, Check methods & Reaction plans.

It standardize the manufacturing process. Helps to produce consistent and predictable Quality. Enhance the Customer confidence. It is a requirement of the TS 16949 standard

Why do we need Control Plan?

Why Control Plan ?


What will happen………

Don’t know what to check, how to check and when to check to control process

Product quality depends on individual’s discretion

Don’t know what to do when some thing goes wrong.

Result in inconsistent and unpredictable product quality.

Low confidence level of customer.

Without Control Plan ?


Product Process

090- Polish journalsSurface

finish

CharacteristicProcess / Operation number

Process / operation

description

Special characteristic

class

Product / Process

specification / tolerance

Proc. Doc. 3800 -090

What to check ?

How important it is …?

Example : Polish Crankshaft

Control Plan - Example

Pakistan Institute of Quality Control How to check ?

Size Freq.Sample

5 journals

every 5th

crankshaft

Evaluation / measurement

technique

Surf tester (Tylor hobson)

Control Method

SPC (X bar-R chart), operator verification of

belt and machine setup

Reaction Plan

100 % inspection of previous 5

crankshaft,replace belts/readjust

machine, notify line leader

How many and when to check ?

What to do when some thing is wrong ?

Example : Polish Crankshaft

Control Plan - Example


Linkage FLOW CHART

CONTROL PLAN

PFMEA

PROC DOC

• Graphic description of the process flow

• Each operation listed

• Describes what can go wrong at each operation

• Pro-active tool

• How to control each factor affecting quality

• What to do if something is wrong

• Detailed process steps• Gauges, tools, methods• Specifications, limits,

acceptance criteria

Linkage with Key Docs.


Gauging Mistake proofing

CONTROL PLAN

Non conformance reports Proc. docs.

Training SPC Control chart

Other Docs. Or Activities


Control Plan Columns’ description and usage 1. Category : Prototype,Pre launch or production

2. Control Plan number : Control plan number should be linked with Flow chart and Process documentation for each station /

operation3. Part name / latest change level : verify the part name, latest change

level indicates the number of times document is changed4. Operation description : Indicates the name of particular operation.5. Supplier Plant : Name of the plant preparing and using control Plan.6. Key contact : Person responsible for control plan7. Core team : indicates the name of individuals of cross functional team

responsible for latest revision.8. Supplier approval: Check for the sign and date of approving authority. 9. Date (Orig.) : is the date of compilation of original control Plan10. Date (Rev) : is the latest revision date11. Customer / other approvals : approvals from customers12. Process / operation number : this item number is referenced from the

Process Flow chart and Process FMEA.

Control Plan - Columns Description


Control Plan Columns’ description and usage 13. Process name/ operation description : this column indicates all

important operational steps14. Machine, device,Jig,Tools : For each operation the processing

equipment e.g. machine, jig or other tools are identified 15. Product characteristics : are the features or the properties of a part that

are described on drawing or engineering specifications e.g. journal diameter, deck height, surface finish e.t.c.

16. Process characteristics : are the process variables that have a cause and effect relation with identified product characteristic e.g. concentration of chemical, washer temperature and cycle time are process characteristics in washing operation and they have cause and effect relation with cleanliness (product characteristic).

17. Special characteristic class : referenced from customer drawings, specifications, non conformance and warranty data, and FMEA. COER uses “Critical/safety” and “major” class

Control Plan - Columns Description


Control Plan columns’ description and usage18. Specification / tolerances :Product and process characteristics are required

to be controlled, check the specifications of these characteristics in Spec./ tolerance column. If specs. are referred to Proc doc.,check the related proc. doc.

19. Evaluation/ measurement technique :Identifies the measurement system e.g. gages, fixtures or test equipment. Make sure that the indicated gage is available at your station, also check for valid calibration

20. Sample size / frequency :Follow the sample size and frequency indicated in the control plan for inspection.

21. Control method column gives the brief description of how the operation will be controlled. For example : Operations may be controlled by SPC-control charts, 100% inspection, sampling inspections or mistake proofing in tooling etc. Use the mentioned control.

22. Reaction plan specifies the corrective actions/ Steps to be initiated when nonconformance is observed. Reaction may be Scrap, Hold, Rework, Notify supervisor, reset machine e.t.c.

Control Plan – Columns Description


Changing Control Plan :

Control Plan is a living document and should be updated to reflect the changes in product / process characteristics, control methods and characteristic measurements

If something is wrong in your Control Plan, it MUST be changed

Take a copy of the Control Plan and note the changes Give the copy with changes to your Team Leader,

Supervisor or Quality Assurance Changes will be reviewed and incorporated .New

document will be issued in 1 or 2 weeks.

Updating Control Plan


Expectations

We need to review existing control plans and create new Control Plan where ever necessary by the end of July’2003

1 or 2 volunteers are required per team to help Team volunteers will have to help Quality Engineer to

review measurement techniques, gauges, frequency of checking, control methods and reaction plans.

Team volunteers will work in Cross functional team to formalize the Control Plan

Control Plan - Expectations


?

Control Plan


Practice Session :

Make groups and create control plan for any process or operation.

Must indicate the Process/ operation name, product / process characteristic, Evaluation/ measurement techniques, frequency of checking, control method and reaction plan.

Control Plan – Practice Session

Documents

FMEA