tidyfault

R Package for tidy Fault Tree Analysis (FTA)!

Uses tidyverse, tidygraph, and QCA packages, among others, to visualize fault trees, identify minimal cutsets, and other quantities of interest.

Basic Usage

How do we use tidyfault to analyze fault trees?

Load Packages and Data

Let's start by loading our dependencies!

# Load dependencies
library(tidyfault)
library(tidyverse)
library(QCA)

Next, let's get some fake data to work with, including nodes and edges in our fault tree.

#Load example data into our environment
data("fakenodes")
data("fakeedges")

Workflow (Step-by-Step)

Finally, let's demonstrate the basic workflow for tidyfault!

First, we...

1. curate() a list of gates in the fault tree;

mygates = curate(nodes = fakenodes, edges = fakeedges)

2. use equate() to find the boolean equation for the fault tree;

myequation = mygates %>% equate()

3. formulate() that equation into an R function we can use;

myfunction = myequation %>% formulate()

4. calculate() all the truth table of all possible combinations of events and the outcome each leads to.

mycombos = myfunction %>% calculate()

5. concentrate() our truth table into the minimum cutsets, the smallest sets of events necessary to cause system failure. This function uses boolean minimalization to find the minimum cutsets.

mymin = mycombos %>% concentrate()

6. tabulate() up our minimum cutsets and how coverage they have over the total paths to failure found with calculate().

mytable = mymin %>% tabulate()

Workflow (All at Once!)

Or, we can do this all in one fell swoop!

Let's extract the minimum cutsets from our fault tree data!

# Start by curating the gates...
mytable = curate(
  nodes = fakenodes, 
  edges = fakeedges) %>%
  # Now apply our next functions
  equate() %>%
  formulate() %>%
  calculate() %>%
  concentrate() %>% 
  tabulate()

Questions?

Contact: Timothy Fraser, PhD (timothy.fraser.1@gmail.com)