reliability 0.5.3

Reliability Engineering toolkit for Python

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.

Key features

• Fitting probability distributions to data including right censored data
• Fitting Weibull mixture models
• Calculating the probability of failure for stress-strength interference between any combination of the supported distributions
• Support for Exponential, Weibull, Gamma, Normal, Lognormal, Loglogistic, and Beta probability distributions
• Mean residual life, quantiles, descriptive statistics summaries, random sampling from distributions
• Plots of probability density function (PDF), cumulative distribution function (CDF), survival function (SF), hazard function (HF), and cumulative hazard function (CHF)
• Easy creation of distribution objects. Eg. dist = Weibull_Distribution(alpha=4,beta=2)
• Non-parametric estimation of survival function using Kaplan-Meier and Nelson-Aalen
• Goodness of fit tests (AICc, BIC, AD)
• Probability plots on probability paper for all supported distributions
• Quantile-Quantile plots and Probability-Probability plots
• Reliability growth, optimal replacement time, sequential sampling charts, similar distributions
• Physics of Failure (SN diagram, stress-strain, fracture mechanics, creep)
• Accelerated Life Testing probability plots (Weibull, Exponential, Normal, Lognormal)
• Accelerated Life Testing Models (Exponential, Eyring, Power, Dual-Exponential, Power-Exponential).
• Mean cumulative function for repairable systems

Installation and upgrading

To install reliability for the first time, open your command prompt and type:

pip install reliability

To upgrade a previous installation of reliability to the most recent version, open your command prompt and type:

pip install --upgrade reliability

Documentation

Check out readthedocs for detailed documentation and examples. If you find any errors, have any suggestions, or would like to request that something be added, please email me: [e-mail].