[R] Please help(urgent) - How to simulate transactional data for reliability/survival analysis

Boris Steipe boris.steipe at utoronto.ca
Wed Jun 28 11:21:15 CEST 2017

In principle what you need to do is the following:

 - break down the time you wish to simulate into intervals.
 - for each interval, and each failure mode, determine the probability of an event.
   Determining the probability is the fun part, where you make your domain
   knowledge explicit and include all the factors into your model: cumulative load,
   failure history, pressure, temperature, phase of the moon ...
 - once you have a probability of failure, use the runif() function to give you
   a uniformly distributed random number in [0, 1]. If the number is smaller than
   your failure probability, accept the failure event, and record it.
 - Repeat many times.

Hope this helps.

> On Jun 27, 2017, at 10:58 AM, sandeep Rana <sandykido at gmail.com> wrote:
> Hi friends, 
> I haven't done such a simulation before and any help would be greatly appreciated. I need your guidance.
> I need to simulate end to end data for Reliability/survival analysis of a Pump ,with correlation in place, that is at 'Transactional level' or at the granularity of time-minutes, where each observation is a reading captured via Pump's sensors each minute.
> Once transactional data is prepared I Then need to summarise above data for reliability/ survival analysis. 
> To begin with below is the transactional data format that i want prepare: 
> Pump-id| Timestamp | temp | vibration | suction pressure| discharge pressure | Flow 
> Above transactional data has to be prepared with below failure modes
> Defects :
> (1)    Cavitation – very high in frequency but low impact
> (2)    Bearing Damage – very low in frequency but high impact
> (3)    Worn Shaft – medium frequency but medium impact
> I have used survsim package but that's not what I need here. 
> Please help and guide. 
> Regards,
> Sandeep 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

More information about the R-help mailing list