Businesses today are having to ask themselves many questions in order to survive the economic downturn:
* How do you compete in this environment?
* What does it take to obtain business from an existing or prospective customer?
You can say that if you knew the answer to that, you wouldn’t be struggling as hard as we are! Yet we need to recognize that there needs to be a competitive edge to win that next order. WHAT IS IT? Part of it is the mentality and capability to know the two edges of the sword to achievement:
* How well do you know your customer or the prospect?
* How well do we know ourselves?
We wouldn’t start a trip or begin to work on something unless we had a plan, and the subsequent measurement points to ensure accomplishing what we set out to.
How can you drive your business without a strong commitment to Performance Measurements? Think about the following:
* Have we met the expectations of our external and internal customers? What did that bring to us? How do we know – what is the mechanism that measures that?
This only the beginning. What measure have you put in place to ensure success?
Chi Squared Distribution for Reliability Demonstration Testing
When planning a Reliability Demonstration Test (RDT), your objective is to demonstrate a certain reliability (or MTBF) at a certain Confidence Level (CL).
If you want to determine what MTBF at a particular CL you have demonstrated, if you tested T number of hours, you would use the formula listed below.
Of course, the actual test time would be dependent upon the Acceleration Factor (AF) and the number of samples on test.
The AF will be determined from the acceleration of environment, duty cycle, and/or electrical parameters (voltage, current, or power).
A RDT will demonstrate that based upon the test results, the true population MTBF is at least Theta hours at a (1-alpha) CL.
The demonstrated MTBF (Theta) for the specified CL will be calculated using the following formula:
Theta = 2 * T / Chi SQ [(2r+2), alpha]
Theta = Demonstrated MTBF
T = Test time X Number of test items X AF
Chi SQ = Chi Squared distribution, the one used because
it best fits our demonstration model
Alpha = (1 – C.L.)
r = number of failures
2r+2 = Chi SQ degrees of freedom (Time terminated test)