0 time failure

[maudley]

I am measuring the time it takes for a system to reach a certain level of deterioration.

The system may surpass the level of deterioration immediately after a renewal / maintenance and therefore the time to this deterioration will be 0.

My times to failure are as follows:

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6.20000 23.80000 24.80000 46.40000 51.50000 56.00000 59.50000 64.60000 72.50000 74.00000 78.30000 79.30000 84.80000 91.00000 100.20000 102.90000 104.40000 109.90000 113.80000 123.30000 123.60000 132.40000 133.00000 137.80000 157.80000 165.00000 172.00000 174.30000 182.00000 182.00000 183.30000 184.70000 184.80000 188.80000 189.00000 189.40000 198.00000 201.40000 201.70000 203.00000 208.00000 212.30000 213.70000 214.80000 215.50000 215.50000 220.70000 224.00000 225.30000 229.00000 238.00000


I am using Reliasoft Weibull ++ to analyse my times to failures and I have found that I cannot analyse them properly unless I change the zeros to 0.001 I'm not convinced this is the right thing to do, have any of you encountered zero time failures before?

How should I deal with them?

In reliasoft Weibull ++ the probability plot changes when zeros are used but the parameters do not which I really cannot get my head around.

Thank you in advance.

 

[BigInch]

If that were true, the theory would ask why you bother to do maintenance on the device. It sounds like a case of, if its not broke, don't fix it... replace it.

Anyway, what question are you attempting to answer when you analyze all that data? Average time to failure? Number of devices failing within a given time?

Devices that immediately explode after maintenance, just add to the average time, or distribution calculation. With their zero values they just pull the range downward.

Only put off until tomorrow what you are willing to die having left undone. - Pablo Picasso