Imagination at work

Reliability: Myths & Realities

Melanie Cox May 5th 2015

Melanie Cox Principal Reliability Engineer/ Design for Reliability Leader

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Business & General Aviation portfolio

3

Turboprops Light jets Mid-size jets Large cabin

M601 H80 family

CFE738 CF34

Passport HF120

P r o d u c t s

S e r v i c e a n d S u p p o r t

A proactive, personal

relationship that’s

simple and easy to do

business with.

Highly reliable

engines, with service

offerings that give you

peace of mind.

Customer

Experience

Lifecycle Value

A comprehensive

support network that

keeps you flying.

Rapid Response

What is Reliability?

The probability that equipment will not suffer a failure

over a given length of time and with a defined set of

usage conditions.

Reliability

Environment

Time

(life)

Probability

Logistical

Mission (Dispatch)

• Probability of being failure free in a given set of conditions

• Probability of performing a function over a specified mission

Two sub-sets of this definition:

What is Reliability?

Customer Requirements

Maintenance Resources

Regulatory Requirements

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Engine Reliability vs Time

1973 1978 1983 1988 1993 1998 2003 2008 2013

Ave. Interval between engine shut-downs

% of North Atlantic flights on 2 engine aircraft 0% in 1983

30% in 1989

56% in 1994

77% today 67% in 1997

What is included in Logistical Reliability? • All failures (not just mission critical)

• All time units (not just mission time)

• Any failure that requires maintenance action

Reliability Theory vs Field Reliability

Reliability theory based on “part count” concept

Less Reliable

More Reliable

Reliability Theory vs Field Reliability

4 parts where the

environment is understood

and the design / analysis

process for designing that

part is mature

1 part that

was not

designed for

the correct

temperature

In-service unreliability typically driven by a small number of

items that are not able to fully withstand the field usage

conditions for the required time.

Less

Reliable

More Reliable

Reliability Prediction vs. Field Data

0.00%

20.00%

40.00%

60.00%

80.00%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0% In theory, reliability is a

function of the number of

parts in the system. Each

component contributes to

failure rate in proportion to

its complexity / number of

parts

In service, unreliability is

dominated by a single

component. Predicted

contribution < 1%, actual

contribution >70%.

Reliability Theory vs Field Reliability

• Field reliability performance is driven by our ability to:

–Understand the operating environment and duty cycle before

the product enters service and

– Design and manufacture the correct product for those

conditions

Which system is more reliable?

Compone

nt A

Two components –

both must function for

the system to function

Compone

nt B

Compone

nt A

Compone

nt B

Compone

nt A

Compone

nt B

Four components, one

“component A” and one

“component B” must

function for the system

to function

Less permutations for system success!

How is Reliability Measured?

MTBF (Mean Time/Cycles Between Failures): how often a repairable item fails defined by the average

interval between failures.

MTBF: A motor is repaired and returned to service six times

during its life and provides 45,000 hours of service. What is the

motor’s MTBF?

hours7,5006

45,000

failuresof#

timeoperatingTotalMTBF

Example:

How is Reliability Measured?

Failure rate (): 1/ MTBF - the expected number of

failures per a measure of the length of operation (time or

cycles).

hours

failuresRateFailure

7*24*1000

2 hourfailures /

000,168

2

= 1.19E-5 failures/hr

1000 power meters were used constantly for a week. 2

meters fail. What is the Failure Rate?

Failure Rate (for constant failure rate) Example:

Example:

When MTBUR MTBF

MTBUR = Mean Time Between Unscheduled Removals

No Fault Found

Removals

Convenience Removals

Indication vs Real Fault

MTBUR < MTBF

How is Reliability Measured?

Reliability: probability of

being failure free over a given

time. For a constant failure

rate: R = e-t

Probability of failure:

how likely an item is to

fail over a given time

F(t) =1-R.

Reliability Example: If failure rate for the power meters is 1.19e-5

failures / hour, what is the reliability of a single meter over one week?

R = e-t

R = e-(1.19e-5 x 24 x 7) e-1.99e-3 = 0.998 or 99.8%

Probability of Failure Example: What is the P(fail) for the above meter

over the same duration?

P(fail) = 1-R = 2e-3 or 0.2%

NB: For very small failure rates, P(fail) approximates to t:

1.19e-5 x 24 x 7 = 1.999e-3

Examples

Product Life Phases

MTBF and Failure Rate metrics assume that failure rate is constant

Time (Product Life)

In

sta

nta

ne

ou

s

Fa

ilu

re R

ate

At the beginning of product

life, failure rate is decreasing

as weaker components fail

(known as “infant mortality”)

and are re-designed so that

overall product reliability

improves.

Towards the

end of product

life, failure rate

increases as

components

start to

experience

“wear out”

After the initial break-in period, failure

rate reaches a constant value for what is

known as the “useful life” of the product

True or False?

Time (Product Life)

In

sta

nta

neo

us

Fa

ilu

re R

ate

Life vs. Reliability

Q: If a component has an MTBF of 20, 000 hours,

what do we know about the component’s life?

Nothing! Component life is the expected usage time

that the component should be designed for.

Life & Reliability are connected, but not the same

If the MTBF for an component is 100,000 hours...

Reliability as a Function of Mission Time t (Exponential Distribution)

36.8% probability of survival past a time of one MTBF

Mission Length

(hours)

Reliability*

1 000 99.0 %

10 000 90.5 %

50 000 60.7 %

100 000 36.8 %

Reliability vs. Life Consider a Mechanical Pencil:

Reliability

• Failure: lead breaks

• How do I “maintain” the

pencil after a failure?

• What factors would influence

the reliability of the pencil?

Life:

• What affects the life of the

pencil? How can I extend

this?

Reliability vs. Life Contrast to a Traditional Wooden pencil:

• What’s different about

maintaining this pencil?

• Can I extend the life?

What effect does this have?

where:

• MTBF = Mean Time Between Failure

• MTTR = Mean Time To Repair & Return to Service

The probability that the product is ready to serve

Mean Availability (uptime / total time) = MTBF

MTBF + MTTR

Availability

The ability of an item to be preserved or restored when

prescribed procedures and resources are used to perform

maintenance

Maintainability

Corrective Maintenance

Preventative Maintenance

Reliability Centered

Maintenance

Intelligent maintenance

Full flight data to map

degradation vs. specific

parameters

Repair a fault

Take action before a fault occurs

Statistically describe failures &

plan to prevent faults occurring

Maintainability: On Condition vs Hard Time

Effectiveness of hard times

depends on population

variation

P(fail) = 0.021 @ 4300

P(fail) = 0.262 @ 4300

10% expected to function

@ 6450

10% expected

to function @

8500

Cost Trade Analysis

Cost of failure

& repair

Cost of

maintenance:

Total cost

Co

st

Time

Optimum time for

scheduled

maintenance

Cost of Operation per Hour vs. Time

Optimum maintenance time is at the beginning of wear-out

failures

Questions?

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