AGMA 07FTM19-2007 pdf free.How to Determine the MTBF of Gearboxes Dr. Gerhard G. Antony, Neugart USA LP.
The fundamental first step in detemiining the reliability and life of a widget is to observe a representative set of samples, a “population” of widgets and record the failures over a certain time frame.
The collected data will show a certain number of failures over an observed time period. An absolute number of failures has no real practical meaning; it atways has to be related to the observed population size. This is expressed by the failure rate.
Failure rate is the relative frequency at which a component or system fails in a given time i.e., failures! minutes, hours, years or within a certain time related measure such as distance i.e., failures/miles (in automotive field), or per operating cycles such as failures in 1 million revolutions (bearings) etc. Aswe can see, it is not an absolute number of units failed but rather a relative number, related to the size of the observed tested number of units, population of products, see figure 1.
It would be more exact to call it the relative failure rat&; because the value is related to the overall observed population, it assumes a value between 0 (0% failures) and 1 (100% failures per hour). This relative failure rate can be recorded at regular time intervals (important in where we want find out if and how the failure rate is changing over the life time) or just record it for a predefined period such as the “design life” the widget, – this would mean, we assume that the failure rate is constant during this period.
Example iPod:
(- source: “Applelnside” July 272006 reporting, under headline “iPods built to last 4 years”)
“Apple spokeswoman Natalie Kerris recently told the Chicago Tribune that iPods have a failure rate of less then 5%. which she said is “fairly low” compared with other consumer electronics.
However, a survey conducted by Macintouch” last year found that out of nearly 9,000 iPods owned by more than 4,000 respondents, more than 1400 of the players had failed. The survey concluded that the failure rate was 13.7 %, stemming from an equal mix of hard drive and battery related issues”
Remark:
Based on the numbers, the actual failure rate should yield to FR = 1400/9000=0.155 or 15.5% for the observed time interval, which can be interpreted that 15.55% — 13.7% = 1.8% failed for some other reason than the listed. Other explanations are also possible however the survey does not list any reasons.
Is Mrs. Kerris from Apple correct with the 5% value over the design life or are the conclusions of the survey with 13,7% correct?
Here are some important questions before we take sides:
Are both talking about the same type of failures? Does Apple consider the necessity to replace the battery a failure? How many units were surveyed by Apple? Is the population of 9000 samples in the survey representative? (Apple ships in excess of 10 million units a quarter.) What was the real usage time or reference time of both observations? Does the statement built to last 4 years” means 4 years 24/7 usage, or for instance only 4 hours a day usage say 6 days a week (duty cycle)?
None of the above two failure rates gives any specific information about these important basic factors, neither about the conditions under which the data were collected. Let us assume that the survey was based on a 12 hour daily usage over a 2 year period, the failure rate, should be calculated as:FR = 1 400 failures / 9000 units (2 years 365 days(12 hrs)) = 0.000017757 /hour
The example above highlights the main difficulty of the reliability /life calculation and the main source for misrepresentations namely the selection of the population, the observed time interval and failure mode,etc.AGMA 07FTM19 pdf download.