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MTBF Estimation

Mean Time Between Failures

The Mean Time Between Failures (MTBF) is a methodology used to estimate the number of failures expected in a product. The analysis examines the rate of random failures, excluding systematic defaults caused by design misconceptions, software errors, manufacturing defects, or wear at the end-of-life product. This method takes into account a given environment.
The MTBF measures the average time, in hours, an electrical or mechanical system stays operational between failures. This analysis applies to repairable equipment. 
The MTBF figure can be of significant value to a potential customer at the time of a transaction. Without this data, the product could be rejected.
The equivalent metric for non-repairable systems is MTTF (Mean Time To Failure), which determines how long a product can be used before its useful life is over.

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Mean Time To Failure

Mean Time To Failure is a predictive method of reliability for non-repairable parts. The average time for the expected first failure of a piece is estimated using this calculation. 
MTTF is a statistic that estimates the average value over a long period on several units.

Mean Time To Repair

Mean Time To Repair refers to the average time required to repair a defective product by replacing a faulty hardware part. 
Thus, the MTTR of a product could be considered the average time to evaluate a failure and replace the corresponding defective components.

Prediction methods 

In today's competitive electronic products market, having higher reliability MTBF MTTF than competitors is a factor for success. For a highly reliable product, consideration of reliability issues should be integrated from the beginning of the design phase. This leads to the concept of reliability prediction.

MIL-HDBK-217F Predictive Method

MIL-HDBK-217, Reliability Prediction of Electronic Equipment, is well-known in the military and commercial industries. It is probably the most internationally recognized empirical prediction method by far. The MIL-HDBK-217 predictive method consists of two parts: one is known as the parts count method, and the other is called the part stress method.
The parts count method assumes typical operating conditions of parts. 
The part stress method requires specific part complexities (called Pi factors). Application stresses, ambient temperature, various electrical stresses, operation mode, and environment (called reference conditions).

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Telcordia SR-332 Predictive Method

The Telcordia SR-332 Standard assumes a serial model for electronic parts addressing failure rates at both the infant mortality and the steady-state stage with Methods I, II, and III.

Method I is similar to the MIL-HDBK-217F parts count and part-stress procedures. The standard provides the generic failure rates and three-part stress factors: part quality factor (πQ), electrical stress factor (πS), and temperature stress factor (πT). 
Method II is based on Method I predictions with data from laboratory tests performed by specific SR-332 criteria. 
Method III is a statistical prediction of failure rate based on field tracking data collected by specific SR-332 criteria.

MIL-HDBK-217F is a method used in the military field, so it is more conservative than the commercial standard. More factors that may affect the failure rate are considered in MIL-HDBK-214.

Pi factors:

The Pi factor illustrates the quality control over product lifecycle reliability MTBF MTTF. Each model has its own failure rate equations. Multiple Pi factors are used to calculate the failure rate of a part. Each parameter impact on the values of one or more Pi factors.

  • πS is the stress factor

  • πT is the temperature factor

  • πE is the environmental factor

  • πQ is the quality factor

  • πA is the adjustment factor

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Nonelectronic Part Reliability Data

Nonelectronic Parts Reliability Data (NPRD) provides failure rate information for mechanical, electromechanical, and electronic assemblies. The database describes field experience in military, commercial, and industrial applications not covered by MIL-HDBK-217, Reliability Prediction of Electronic Equipment. Data includes part descriptions, quality level, application environments, point estimates of failure rate, data sources, number of failures, operating hours, and part characteristics.

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Failure Rate (F.R.)

The failure rate is a function that describes the number of defaults that can be expected over a given time. Failure rates are not constant throughout the lifecycle of electronic equipment. This function is part of the reliability MTBF MTTF analysis and follows a bathtub curve divided into three time periods:


Infant Mortality: The F.R. is high but decreases rapidly. Calculation methods assume that this period is the first year of operation.


Steady-state: failures occur at a constant rate (steady-state failure rate). MIL-HDBK 217F Standard assumes that F.R. is always a constant. On the other hand, Telcordia SR-332 Standard predicts that this is the period after the first year of operation (8760-10000 hours).


Wearout: The failure rate increases rapidly. Wearout does not occur during the service life of an electronic device, which is about 20 years. Telcordia SR-332 does not take into account this period.

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Bathtub curve

Failure In Time (FIT)

Failures in time are an alternative form of displaying a result of reliability MTBF MTTF prediction. It denotes the expected number of failures per billion hours of an operating part or device. This term is most used by the semiconductor industry. 
The failure rate (F.R.) is expressed in units of time. The hour is the most common unit in practice. Most values are expressed as failures per millions of hours of operation for a commercial/industrial product.

Factors affecting F.R.

  • Operating requirements 

  • Electric stress

  • Temperature

  • Environment

  • Quality of components

A high failure rate is indicative of low MTBF

The main achievement of reliability MTBF MTTF is to assess the success of a product to establish potential failures as early as the product's life cycle and then take appropriate action to make the necessary improvements. 

It is never too late to enhance the reliability of a product. Remember: modifications are less costly at the start of design than later when the product is in production.

Information needed for MTBF MTTF analysis

The following is the information provided for the reliability MTBF MTTF analysis: 

  • Bill of material

  • Preferred calculation method

  • Preferred environment

  • Temperature range 

MTBF Prediction Report Contents

The comprehensive reliability MTBF MTTF prediction report, based on specific requirements, includes the following information:

  • Prediction parameters

  • Standard used

  • Environment applied

  • Summary of results providing reliability MTBF MTTF in hours, years, and FIT.

  • Comprehensive reports showing component failure rates and MTBF for three temperatures (optional)

  • Failure Rates Vs. Time chart

  • MTBF Vs. Temperature chart

  • Photo(s) of the equipment or product analyzed (optional) 

We help you with a reliable product:

  • Assessment of the reliability of electrical components 

  • Estimate the reliability of mechanical parts

  • Improve the reliability of your product

  • Create a reliability test plan 

  • Provide a complete reliability report

For a reliability MTBF MTTF estimation, contact us at

MTBF Prediction. Expertemc Engineering Consultant
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