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reliability is a Python library for reliability engineering and survival analysis. It significantly extends the functionality of scipy.stats and also includes many specialist tools that are otherwise only available in proprietary software.

If you frequently use the Python Reliability Library, please consider filling out a quick survey to help guide the development of the library and this documentation.

Contents:

Quickstart & Intro

• Quickstart for reliability
• Introduction to the field of reliability engineering
• Recommended resources

Parametric Models

• Equations of supported distributions
• Creating and plotting distributions
• Fitting a specific distribution to data
• Fitting all available distributions to data
• Working with fitted distributions
• Mixture models
• Competing risks models
• DSZI models
• Optimizers

Probability Plotting

• Probability plots
• Quantile-Quantile plots
• Probability-Probability plots

Non-parametric models

• Kaplan-Meier
• Nelson-Aalen
• Rank Adjustment

Accelerated Life Testing

• What is Accelerated Life Testing
• Equations of ALT models
• Getting your ALT data in the right format
• Fitting a single stress model to ALT data
• Fitting a dual stress model to ALT data
• Fitting all available models to ALT data
• What does an ALT probability plot show me

Importing and converting data

• Datasets
• Importing data from Excel
• Converting data between different formats

Repairable systems

• Reliability growth
• Optimal replacement time
• ROCOF
• Mean cumulative function

Reliability testing

• One sample proportion
• Two proportion test
• Sample size required for no failures
• Sequential sampling chart
• Reliability test planner
• Reliability test duration
• Chi-squared test
• Kolmogorov-Smirnov test
• Likelihood plot

Physics of failure

• SN diagram
• Stress-strain and strain-life
• Fracture mechanics
• Creep
• Palmgren-Miner linear damage model
• Acceleration factor
• Solving simultaneous equations with sympy

Other functions

• Stress-Strength interference
• Similar Distributions
• Make right censored data
• Make ALT data
• Crosshairs
• Distribution explorer
• Histogram

Reliability Theory

• What is censored data
• How are the plotting positions calculated
• How does Least Squares Estimation work
• How does Maximum Likelihood Estimation work
• How are the confidence intervals calculated

Administration

• Changelog
• Development roadmap
• Copyright information
• Citing reliability in your work
• Contributing
• How to get help
• How to donate to the project
• About the author
• Credits to those who helped
• Logo

API reference

• API Reference
  • ALT_fitters
    • Fit_Everything_ALT
    • Fit_Exponential_Dual_Exponential
    • Fit_Exponential_Dual_Power
    • Fit_Exponential_Exponential
    • Fit_Exponential_Eyring
    • Fit_Exponential_Power
    • Fit_Exponential_Power_Exponential
    • Fit_Lognormal_Dual_Exponential
    • Fit_Lognormal_Dual_Power
    • Fit_Lognormal_Exponential
    • Fit_Lognormal_Eyring
    • Fit_Lognormal_Power
    • Fit_Lognormal_Power_Exponential
    • Fit_Normal_Dual_Exponential
    • Fit_Normal_Dual_Power
    • Fit_Normal_Exponential
    • Fit_Normal_Eyring
    • Fit_Normal_Power
    • Fit_Normal_Power_Exponential
    • Fit_Weibull_Dual_Exponential
    • Fit_Weibull_Dual_Power
    • Fit_Weibull_Exponential
    • Fit_Weibull_Eyring
    • Fit_Weibull_Power
    • Fit_Weibull_Power_Exponential
  • Convert_data
    • FNRN_to_FR
    • FNRN_to_XCN
    • FR_to_FNRN
    • FR_to_XCN
    • XCN_to_FNRN
    • XCN_to_FR
    • xlsx_to_FNRN
    • xlsx_to_FR
    • xlsx_to_XCN
  • Datasets
  • Distributions
    • Beta_Distribution
    • Competing_Risks_Model
    • DSZI_Model
    • Exponential_Distribution
    • Gamma_Distribution
    • Gumbel_Distribution
    • Loglogistic_Distribution
    • Lognormal_Distribution
    • Mixture_Model
    • Normal_Distribution
    • Weibull_Distribution
  • Fitters
    • Fit_Beta_2P
    • Fit_Everything
    • Fit_Exponential_1P
    • Fit_Exponential_2P
    • Fit_Gamma_2P
    • Fit_Gamma_3P
    • Fit_Gumbel_2P
    • Fit_Loglogistic_2P
    • Fit_Loglogistic_3P
    • Fit_Lognormal_2P
    • Fit_Lognormal_3P
    • Fit_Normal_2P
    • Fit_Weibull_2P
    • Fit_Weibull_2P_grouped
    • Fit_Weibull_3P
    • Fit_Weibull_CR
    • Fit_Weibull_DS
    • Fit_Weibull_DSZI
    • Fit_Weibull_Mixture
    • Fit_Weibull_ZI
  • Nonparametric
    • KaplanMeier
    • NelsonAalen
    • RankAdjustment
  • Other_functions
    • crosshairs
    • distribution_explorer
    • histogram
    • make_ALT_data
    • make_right_censored_data
    • similar_distributions
    • stress_strength
    • stress_strength_normal
  • PoF
    • SN_diagram
    • acceleration_factor
    • creep_failure_time
    • creep_rupture_curves
    • fracture_mechanics_crack_growth
    • fracture_mechanics_crack_initiation
    • palmgren_miner_linear_damage
    • strain_life_diagram
    • stress_strain_diagram
    • stress_strain_life_parameters_from_data
  • Probability_plotting
    • Beta_probability_plot
    • Exponential_probability_plot
    • Exponential_probability_plot_Weibull_Scale
    • Gamma_probability_plot
    • Gumbel_probability_plot
    • Loglogistic_probability_plot
    • Lognormal_probability_plot
    • Normal_probability_plot
    • PP_plot_parametric
    • PP_plot_semiparametric
    • QQ_plot_parametric
    • QQ_plot_semiparametric
    • Weibull_probability_plot
    • plot_points
    • plotting_positions
  • Reliability_testing
    • KStest
    • chi2test
    • likelihood_plot
    • one_sample_proportion
    • reliability_test_duration
    • reliability_test_planner
    • sample_size_no_failures
    • sequential_sampling_chart
    • two_proportion_test
  • Repairable_systems
    • MCF_nonparametric
    • MCF_parametric
    • ROCOF
    • optimal_replacement_time
    • reliability_growth
  • Utils