The following note and question appear in my email the other day. I had given the definition of reliability quite a bit of thought, yet have not really thought too much about a definition of ‘product life time’.
Here’s a common problem. You have been tasked to peer into the future to predict when the next failure will occur.
Predictions are tough.
One way to approach this problem is to do a little analysis of the history of failures of the commonest or system. The problem looms larger when you have only two observed failures from the population of systems in questions.
While you can fit a straight line to two failures and account for all the systems that operated without failure, it is not very satisfactory. It is at best a crude estimate.
Let’s not consider calculating MTBF. That would not provide useful information as regular reader already know. So what can you do given just two failures to create a meaningful estimate of future failures? Let’s explore a couple of options. Continue reading Life Data Analysis with only 2 Failures→
During RAMS this year, Wayne Nelson made the point that language matters. One specific example was the substitution of ‘convincing’ for ‘statistically significant’ in an effort to clearly convey the ability of a test result to sway the reader. As in, ‘the test data clearly demonstrates…’
As reliability professionals let’s say what we mean in a clear and unambiguous manner.
I am a rock climber. Climbing relies on skill, strength, knowledge, a bit of luck, and good gear. Falling is a part of the sport and with the right gear the sport is safe.
I do not know, nor want to know, the MTBF (or MTTF) of any of my climbing gear. Not even sure this information would be available. And, all of the gear I use does have a finite chance of failing every time the equipment is in use. Part of my confidence is the that probability of failure is really low. Continue reading Do not want equipment failures→