RePyability

Reliability Engineering Tools

This is a series of tools created to make an open source set of methods to be used by reliability engineers to make it more accessible for students right through to practicing professionals.

RePyability builds and analyses systems as reliability block diagrams (RBDs), taking already-fitted lifetime models (from surpyval or anything exposing sf/ff) as its components:

• Fault trees: static fault trees (OR, AND and VOTE gates, repeated events) evaluated exactly, with cut sets, importance measures and conversion to and from block diagrams.
• Reliability: exact system reliability, hazard and conditional survival; MTTF with confidence intervals; BX life; uncertainty intervals from uncertain (fitted) component models.
• Importance: Birnbaum, improvement potential, RAW, RRW, criticality, Fussell–Vesely, structural importance and parameter sensitivity.
• Live state: reliability, remaining life and importance given each component's current age, and covariate-dependent components.
• Redundancy and dependence: cold, warm and hot standby; repeated nodes; load sharing; beta-factor and MGL common-cause groups.
• Repairable systems: exact long-run availability, failure frequency and MUT/MDT/MTBF; simulated availability over time with criticality measures.
• Simulation: seeded Monte-Carlo run to a tolerance, antithetic pairs, parallel runs, and comparisons of designs with common random numbers.
• Cost, design and maintenance: exact and simulated running costs, including scheduled (age or block) preventive replacement at system level, with its intervals chosen for a cost or availability target, hidden failures found by periodic inspection, with the test intervals chosen for a PFDavg target, the total cost of ownership, optimal redundancy allocation (for the lowest total cost of a repairable system, too), reliability allocation by the classic named methods (equal and ARINC-style apportionment, minimum effort, cost-based), availability allocation to MTTF and MTTR targets, and age-replacement and overhaul policies.

import surpyval as surv
from repyability import NonRepairableRBD

rbd = NonRepairableRBD(
    [("s", "pump1"), ("s", "pump2"), ("pump1", "valve"), ("pump2", "valve"), ("valve", "t")],
    {
        "pump1": surv.Weibull.from_params([100, 2]),
        "pump2": surv.Weibull.from_params([100, 2]),
        "valve": surv.Weibull.from_params([200, 1.5]),
    },
)
rbd.sf(50)                     # 0.839: system reliability at t = 50
rbd.birnbaum_importance(50)    # which component matters most

New to reliability engineering? The documentation includes Learn, a short course that teaches system reliability from a single part's lifetime to designing and maintaining whole systems, working every idea out by hand and then with RePyability, with exercises and worked answers.

Install

RePyability can be installed via pip using the PyPI repository

pip install repyability

Documentation

The full documentation — tutorial, user guide, concepts and API reference — is hosted at derrynknife.github.io/RePyability.

It is built with MkDocs from the sources in docs/ and mkdocs.yml, and published to GitHub Pages on every push to master. To build and serve it locally:

pip install -e .[docs]
mkdocs serve            # then open http://127.0.0.1:8000

The source lives in docs/ and mkdocs.yml; start with docs/index.md.

Testing

Run the testing suite by simply executing:

pytest

or use coverage to get a coverage report:

coverage run -m pytest  # Run pytest under coverage's watch
coverage report         # Print coverage report
coverage html           # Make a html coverage report (really useful), open htmlcov/index.html

Pre-commit

TL;DR

• Pip install pre-commit (it's in requirements_dev.txt anyways)
• Run pre-commit install which sets up the git hook scripts
• If you'd like, run pre-commit run --all-files to run the hooks on all files
• When you go to commit, it will only proceed after all the hooks succeed

Why?

To ensure the good code quality and consistency it is recommended that when contributing to this repository to use the provided .pre-commit-config.yaml configuration for the Python package pre-commit (https://pre-commit.com). Upon making a commit, it checks that imports and requirements are sorted, syntax is up-to-date, code is formatted, linted, and statically type-checked, all with the same tools and configurations as one another.