Part 2 of how to measure reliability for part 1 https://www.linkedin.com/pulse/real-reliability-stop-abusing-ammar-alkhaldi-cbbss-

1. Ammar Alkhaldi
Real Reliability
2 April 2016
PART 2: Begin with the end in mind
How to Measure Reliability

2. Use reliability to measure reliability
Sound obvious…
Reliability is probability that a product, system or service
will perform its intended function adequately for a
specified period of time, operating in a defined
operating environment without failure.
So it’s a probability, for specific time (t).

3. Use reliability to measure reliability
Sound obvious…
Reliability is probability that a product, system or service
will perform its intended function adequately for a
specified period of time, operating in a defined
operating environment without failure.
So it’s a probability, for specific time (t).
This summon the magical reliability function
𝑅(𝑡)

4. Reliability function in action
𝑅(𝑡) Vs. MTBF (MTxx)
Or any
another

5. Diode MTTF = 20 YearDiode MTTF = 20 Years
Reliability function in action
 USER B
So the average life of the
population is 20 years, and if
the Standard Deviation = 1
year then 99% of the relays
will fail within 17-23 years.
Now I’ll set my strategy
 USER A
So 50% of the population
will fail after 20 years.
Now I’ll set my strategy
How can “taking MTBF value as it is” lead to wrong strategy

6. Diode MTTF = 20 YearDiode MTTF = 20 Years
Reliability function in action
 USER B
So the average life of the
population is 20 years, and if
the Standard Deviation = 3
years then 99% of the relays
will fail within 17-23 years.
Now I’ll set my strategy
 USER A
So 50% of the population
will fail after 20 years.
Now I’ll set my strategy
How can “taking MTBF value as it is” lead to wrong strategy

7. Diode MTTF = 20 Years
Reliability function in action
 USER C
Will assume:
A. The vendor calculate the MTTF in the right way.
B. Constant failure rate (i.e. exponentially distributed).
How can “taking MTBF value as it is” lead to wrong strategy
𝐹 𝑡 = 1 − 𝑒−𝜆𝑡, MTTF= 1/𝜆 Do the math
Where 𝜆= failure rate, 𝑡 = Time
𝑅 𝑡 = 1 − 𝐹 𝑡
𝑅 1 𝑌𝑒𝑎𝑟 = 1 − (0.0487) = 95.1% Reliability by the first year
𝑅 20 𝑌𝑒𝑎𝑟𝑠 = 1 − (0.632)= 36.8 % Reliability by 20 years

8. Diode MTTF = 20 Years
Reliability function in action
 USER C
Will assume:
A. The vendor calculate the MTTF in the right way.
B. Constant failure rate (i.e. exponentially distributed).
How can “taking MTBF value as it is” lead to wrong strategy
𝐹 𝑡 = 1 − 𝑒−𝜆𝑡, MTTF= 1/𝜆
Where 𝜆= failure rate, 𝑡 = Time
𝑅 𝑡 = 1 − 𝐹 𝑡
𝑅 1 𝑌𝑒𝑎𝑟 = 1 − (0.0487) = 95.1% Reliability by the first year
𝑅 20 𝑌𝑒𝑎𝑟𝑠 = 1 − (0.632)= 36.8 % Reliability by 20 years
IS THIS WHAT EXPECTED BY
20 YEARS MTTF ???

9. Diode MTTF = 20 Years
Reliability function in action
 USER C Now let’s come to the assumptions
Will assume:
A. The vendor calculate the MTTF in the right way.
B. Constant failure rate (i.e. exponentially distributed).
A. Testing 12 diodes for 1month doesn’t reflect 1year reliability nor
introducing all the failure modes, if the data provided by the vendor s
not accurate then this assumption is wrong, using your own field data is
better and reflecting the real running environment, ask the vendor how
the ALTA was done.
How can “taking MTBF value as it is” lead to wrong strategy

10. Diode MTTF = 20 Years
Reliability function in action
 USER C Now let’s come to the assumptions
Will assume:
A. The vendor calculate the MTTF in the right way.
B. Constant failure rate (i.e. exponentially distributed).
B. For electronics components, assuming constant failure can be
acceptable (in fact it’s a random failure rate) since the constant failure
rate phase aka useful life phase can be long enough for the
components to fail due to the random failures before it even reach the
wear out phase.
What if it wasn’t constant failure rate
How can “taking MTBF value as it is” lead to wrong strategy

11. What if it wasn’t constant failure rate
In this turbine’s
winding Example
it’s clear That the
exponential
distribution is not
fitting The failure
data.
In such case we
won’t be able to
determine the
reliability function
given MTBF value
alone.
We need special
tools to find the
𝑅(𝑡) Credit to blog.minitab.com

12. Why vendor still using MTBF ?
20 years MTBF sound much better than “There is
63.2 % chance our component will fail by 20
years”.
Specially if the competitors still using MTBF
furthermore customers even asking for it.

13. Calculating the reliability function

14. Begin with the end in mind
First thing we need to do before measuring
reliability, is to ask this question:

15. Begin with the end in mind
First thing we need to do before measuring
reliability, is to ask this question:
Why are we measuring the reliability ?

16. Begin with the end in mind

17. Begin with the end in mind
Does it really matter ?
Can’t we just measure it now and decide later ?
Actually I might use one tool for multi purposes!

18. Begin with the end in mind
Yes it does matter.
Reliability is a little bit different, We have different
tools, each have its own usage
Does it really matter ?
Can’t we just measure it now and decide later ?
Actually I might use one tool for multi purposes!

19. Begin with the end in mind
Does it really matter ?
Can’t we just measure it now and decide later ?
Actually I might use one tool for multi purposes!
The wrong tool will give a wrong (misleading) result.

20. WHY?
• Preventive Maintenance
• Spare parts strategies
• Inspection scheduling
• Warranty
• Benchmarking
• Risk assessment
• Risk mitigation
WHAT?
• Component/System
• Repairable/Non-Repairable
• HOW?
• Life data analysis (Weibull)
• Reliability Growth
• Reliability Block Diagram (RBD)
• And many other tools

21. If you are interested how to use
some of these tools, stay toned for
the upcoming post.
Salam
Ammar Alkhaldi, CSSBB
How to use reliability tools

22.  NO MTBF Blog http://nomtbf.com/
 SIEMENS Background information on MTBF
 http://www.weibull.com/hotwire/issue22/hottopics22.htm
 http://blog.minitab.com/blog/understanding-statistics/choosing-
the-right-distribution-model-for-reliability-data
References

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