What is BS EN 61649 - Weibull analysis about?
BS EN 61649 is a technical specification that provides methods for analysing data from a Weibull distribution using continuous parameters such as time to failure, cycles to failure, mechanical stress, etc. BS EN 61649 is applicable whenever data on strength parameters, e.g., times to failure, cycles, stress, etc. are available for a random sample of items operating under test conditions or in-service, for the purpose of estimating measures of reliability performance of the population from which these items were drawn.
BS EN 61649 is applicable when the data being analysed are independent, and identically distributed. This should either be tested or assumed to be true (see IEC 60300-3-5). In BS EN 61649, numerical methods and graphical methods are described to plot data, make a goodness-of-fit test, estimate the parameters of the two- or three-parameter Weibull distribution, and plot confidence limits. Guidance is given on how to interpret the plot in terms of risk as a function of time, failure modes, possible weak population, and time to first failure or minimum endurance.
Who is BS EN 61649 - Weibull analysis for?
BS EN 61649 on weibull analysis is useful for:
- Performing life data analyst
- The automotive industry
- The electrical industry
- Quality assurance management
- Mathematicians
Why should you use BS EN 61649 - Weibull analysis?
The Weibull distribution is used to model data regardless of whether the failure rate is increasing, decreasing, or constant. BS EN 61649 gives you guidance on how to perform an analysis using a spreadsheet program. BS EN 61649 provides manufacturers with methods to analyse different failure modes separately and identify a possible weak population.
Using the BS EN 61649 guidelines helps users with the Weibull distribution and can give information on time to analyse failure or minimum endurance. The capacity to assess failure trends and generate failure projections based on known sample data sets is the major benefit of Weibull Analysis. The Weibull distribution is advantageous because of its versatility and ability to be applied efficiently to tiny sample sets.
