MTBF PREDICTION & CALCULATION
Reliability prediction methodology provides the basis for reliability evaluation and analysis. By allowing you to assess the reliability of your design prior to production, reliability predictions enable you to build products with confidence. Reliability prediction techniques encompass a broad range of standards and statistical models. By incorporating all globally accepted standards, Relteck uses PTC (Windchill Quality Solution - Relex) Reliability Prediction software which offers the most comprehensive prediction package available known as the standard in a broad range of industries, with Relex Reliability Prediction you can be assured you are using the trusted brand name in prediction analytic. Relteck will provide training and offers Mean Time Between Failure (MTBF) reliability predictions analysis product that addresses needs of most customers. Upon receiving your product Bill of Material (BOM), Relteck will use advanced reliability software modeling, along with real world data and our expertise, to predict a MTBF for your product. The service includes a comprehensive report & and consultation from one of our reliability experts.
Mean time between failure (MTBF) predictions has many applications including substantiating a design requirement, identifying reliability drivers, making competitive product evaluations, selecting warranty periods, advertising and marketing. Relteck can help you calculate your MTBF.
MIL-HDBK-217F, Telcordia SR-332, Mechanical (NSWC), NPRD95 and 217 Plus are the most popular MTBF prediction standards. Commercial Bellcore TR-332 or the Commercial Telcordia SR-332 are both available for use. A variety of end user environment are provided by each standard to allow tailoring of failure rate data to your product’s market. Prediction using MIL-HDBK-217 or Telcordia® SR332 provides a front-end look at mean time between failure. The model can predict MTBF using as little as the part type and count information. As the design progresses it can be updated to include thermal and piece part circuit stress analysis information. MIL-HDBK-217 is useful for both military and commercial electronics. Telcordia prediction models address commercial electronics only. It has the ability to consider the results of burn-in test, assembly and top assembly test, acceptance test, and field performance data. Hence, it can calculate pre-production, production and operational MTBF.
MTBF Prediction :: Parts Count Analysis
Parts count analysis is a simple and efficient means to calculating system level reliability by using reliability ratings for each component in the system, or sub-system. It is typically conducted early in the design phase to gauge the reliability of the product before prototypes are made.
MTBF Prediction :: Parts Stress Analysis
Parts stress analysis is conducted at a later stage of development and usually provides a lower, and more accurate MTBF figure. Unlike the parts count method, parts stress takes into account a great deal more information about each component, such as:
Component Quality Factor
First Year Reliability Estimates
In order to properly understand MTBF, it’s important to remember these key definitions
MTBF - or Mean Time Between Failures is calculated in hrs and is a prediction of a product reliability.
MTBF = 1/λ (failure rate)
MTTF - or Mean Time To Failure may be substituted in some data sheets for units that will not be repaired
Reliability - is further defined as the probability that given a certain failure rate, a certain number of units will pass (or fail) within a specified period.
Failure Rate - Failure rate is the rate of product failures expressed as a function of time. λ = 1/MTBF
Now that all terms have been defined properly, the relationship between failure rates, predicted reliability and MTBF can be summed up with the exponential formula R (t) = e^ - (t/MTBF) where e = 2.718
The equation is used in this typical MTBF example:
What is the predicted reliability for a unit that has a useful life of 5 years and an MTBF rating of 500,000 HRS?
R = 2.718 ^- (8760*5/500,000) =.916 or 91.6% of the units will still be failure free.
8.4 % will have failed.