MTBF Prediction for Mechanical Design


BQR has two separate applications for predicting the Mean Time Between Failures of a Mechanical Design.

  • CARE-NSWC-98 Standard - the prediction result is an exponential distribution (constant failure rate).
  • CARE-MRS: Mechanical Reliability Simulation tool Weibull, Lognormal, Normal etc. using finite elements and Monte-Carlo techniques.

 

The CARE’s-NSWC 98 Standard
Just as reliability prediction for Electronic equipment requires a set of components with standard failure rates, mechanical equipment does also. BQR has already defined a collection of mechanical components so that their failure rates and MTBF can be calculated according to the standard. These components include Seals, solenoids, gears, fasteners etc. 
  MTBF Prediction for Mechanical Design

CARE’s-MRS application
The Mechanical Reliability Simulation (MRS) module is a tool that performs fast Analytical Reliability Predictions for any type of mechanical system.
MRS analyzes a mechanical system containing elements and subsystems. Each element includes number of input parameters. These input parameters (geometry, material properties, loads, environment, etc.) are defined in the element dialog box. The variations of these input parameters are defined as random input variables and are characterized by their distribution type (Gaussian, Normal, Lognormal, Exponential, Uniform, Weibull, Pareto, Rayleigh) and by their distribution parameters (mean values, standard deviation, etc.). The times of failure for each element are calculated at random (using MonteCarlo simulation). The calculation model includes coupled time dependent failure modes: wear, fatigue, corrosion, and creep. After the calculation of massive randomly time to failure, MRS automatically creates a time to failure histogram, and calculates parameters for all possible distribution types. After which the program selects the optimal distribution type. For this the program takes all standard distributions and examines, using Hi2 test, its compliance with the observed data. The distribution with the greatest significance level is highlighted in the Distribution grid and the corresponding Failure density chart is shown.

 

Features:

  • Faster creation of any type of mechanical assembly by using full range of machine elements, drives/transmissions, bearings, fasteners & actuators.
  • Kinematical links between the elements enabling automatic transmission of full kinematics parameters range including: Torque moments, Speeds and Forces between components – resulting in reduced time-for-input data and user mistakes.
  • Accurate description of real world load condition and material properties by using full range of statistical distribution.
  • MTBF prediction for “Customized” component.
  • Completed material library including full range of properties.
  • Automated generated basic failure modes and failure causes for each mechanical component to be used for FMEA/FMECA, FTA and RBD analyses.
  • Export of Reliability distribution for automatic Preventive Maintenance Optimization performed by apmOptimizer.

for more information click here

 
 
 

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