Reliability Analysis … now what? Part 3

podcast episode with speaker Chris Jackson

This is the third in our webinar series ‘Reliability Analysis … now what?’ The first webinar showed what it means to turn reliability data into something a decision-maker can use. Not a chart. Not a graph. Not a ‘p’ value. Not anything else that you find in a textbook but isn’t useful. Last month’s webinar talked about how the best way to do this is to use computers … but in an easy way! And we talked about creating a ‘posse’ of possible ‘ways’ to explain the data we see. And this webinar is about how we use this thing called Markov Chain Monte Carlo Simulation (MCMC) to create this ‘posse.’ And the ‘posse’ isn’t random … it is based on the ‘likelihood’ of each one being the correct one, which is how MCMC works. [Read more…]

Reliability Analysis … now what? Part 2

podcast episode with speaker Chris Jackson

Last month’s webinar was ‘Reliability Analysis … now what?’ And we showed how to slightly ‘tweak’ all those textbook reliability analyses into USEFUL ACTIVITIES. What good is a 90 % confidence bound on reliability? What does this mean for profit? Or fleet size? Or mission success? We solved this problem by identifying the ‘likely’ ways we can explain our data. In fact – there is a whole bunch of statistics on creating the ‘likelihood’ of an explanation of what we see. We use this ‘likelihood’ in most statistical applications – including those USEFUL ACTIVITIES we discussed above. [Read more…]

Reliability Analysis … now what?

podcast episode with speaker Chris Jackson

Let’s say that you have some ‘reliability guys’ do some reliability analysis on reliability data … and they give you some numbers. Or a plot. Or a curve. Perhaps you are the reliability guy … and you do the analysis – and then what? [Read more…]

So what is up with this ‘Bayesian’ analysis stuff

podcast episode with speaker Chris Jackson

Some of you may have heard of ‘Bayesian analysis.’ You may think this is something fancy that only universities do. Or something we never do because it is all about ‘best guesses.’ Well … neither of these things are true.

Why would you be interested in Bayesian analysis? Simple. It allows you to use EVERY PIECE OF INFORMATION you have. This can be expert judgment. Or it can be test data on a similar ‘thing.’ Or it could be combining test data for one part of your ‘thing’ combined with test data for ‘all of your thing.’ [Read more…]