estimating failure parameters in reliability analysis

Empowering Maintenance & Reliability Decision Makers

© 2009 ARMS Reliability Engineers

Estimating Failure Parameters

Mick Drew – ARMS Reliability Engineers

How important is it to use Failure Parameters in Reliability Analysis and RAMS for

major projects?

Answer: There are different types of Failure Parameters that can be used. There are failure parameters that

are used to assess the reliability of a component or system, and there are failure parameters used to predict

reliability of components or systems.

Assessment: One of the most common parameters used to assess reliability is MTBF. Comparing the MTBF is an

indicator of the time between failures and can also be used to calculate system Availability.

The Mean Time Between Failures is calculated by:- Total Operating hours/No of Failures

The MTBF can be used at equipment level or at System level. The inverse of the MTBF is the Failure rate. For

new projects failure rates can be determined from existing plant, similar plant or there may be published data

availability from various industry bodies. OREDA is often referred to for offshore oil industry, and the GADS

database for more than 6,500 electric generating units. Other published data is available from Reliability Analysis

Centre such as the NPRD handbook for non electronic parts.

Of course the best data is from your own plant or similar plant. In the following I describe the analysis of failure

data for four cases.



In case a system has four failures over the first 70 days of operation. The timeline is shown above. From the

event log the following data is assembled and the MTBF is calculated from 44 operating days divided by 4

failures gives an mtbf of 11 days. Similarly the MTTR the plant is 6.5 days.

In service TTF

Perform

Maintenance Duration

0 7 7 4

11 10 21 5

26 12 38 7

45 15 60 10

Total 44 26

Mean 11 6.5

A maintenance analysis finds the first failure was due to severe aging mechanism, whereby it was decided to

perform a PM task every 15 days.

The resulting timeline is shown in (Case 2) and the timeline shows the first failure eliminated.

15 30 45 60

Up

Down

Case 1



In this case the MTBF has increased from 11 days to 18 days. A dramatic improvement. Or is it?

When we include the planned outages in the calculation as shown in Case 3, the Mean Time Between Outages

has reduced to only 6.7 days. So whilst the failures have reduced the downtime has actually increased.

In

service TTF

Perform

Maintenance Duration

0 15 15 2 PM

17 4 21 5 Repair

26 4 30 2 PM

32 6 38 7 Repair

45 0 45 2 PM

47 13 60 10 Repair+PM

70 5 75 2 PM

Total 47 30

Mean 6.7 4.3

15 30 45 60

Up

Down

15 30 45 60 75

Mtbo=47/7=6.7days

Up

Down

Case 2

Case 3



Investigation work by the Engineering group finds a way to eliminate the Regular PM’S and design out two of the

failures, but the repair time is now greatly increased. But the MTBF increases significantly to 18 days.

Case 4.

In

service TTF

Perform

Maintenance Downtime

0 21 21 24

45 15 60 26

Total 36 50

Mean 18 25.0

15 30 45 60 75

Mtbf=36/2=18days

Up

Down



Discussion of Results

Comparison on the MTBF could indicate that the MTBF of case 4 means that Case 4 is the best case.

Case 1 Case 2 Case 3 Case 4

MTBF (Days) 11 16 6.7 18

This is clearly not the case if one was at all concerned about the amount of downtime.

In order to consider the downtime it is necessary to factor in the MTTR and calculate Availability for each case

which is shown below.

Availability = MTBF/(MTBF+MTTR)

Case 1 Case 2 Case 3 Case 4

MTBF 11 16 6.7 18

Failure Rate 0.09 0.06 0.15 0.06

MTTR 6.5 7.3 4.3 25

Availability 62.9% 68.6% 61.0% 41.9%

From this of course we see that Case 1 is actually better than Case 3 and Case 4 and Case 2 is invalid because the

planned downtime was not taken into account.

Conclusions

• If you are concerned about number of unplanned outages- MTBF can be used as a guide.

• If you are concerned about number of outages- MTBO can be used as a guide.

• If you are concerned about minimising Downtime then Availability can be used as a guide.

• It is very important to consider both planned and unplanned outages when assessing and comparing

systems.

• The use of a fixed time maintenance regime without consideration of operating time is far too

conservative.

• Major projects may start off with maintenance outage data from vendors but the actual outage times

must be determined through maintainability studies that take into account logistics delays, sparing

levels, diagnostic times.

• What about Predicting performance? For the answer to that question we need to go to Reliability

Parameters.

estimating failure parameters in reliability analysis

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