Working with Freetext: Inspired by Verb-Noun Software Approach on Apollo Mission

 We all have seen failures captured in freetext. This is such a common problem that this information is only used to review the shift and then stored never to be used again - the most important feature that has the failure modes!

Back in the 60s, NASA had the reverse problem, they wanted an efficient way to present human commands into a computer to control the spacecraft. They settled on an elegant way of coding things using VERB-NOUN format. OPEN-VALVE, SWITCHON-LIGHT and so on. 

So in failure data, one would usually have a component and its status mentioned in one form or another. One way to encode the freetext into usable data is to use a similar approach. 

Using an online Part-of-Speech (POS) interpreter, one can code the words into three categories, Nouns, Verbs and Adjectives. Adjectives are added to include STATUS words such as loose, damaged and broken. These really come in handy when looking for typical bad actors.

With POS tagging out of the way, all the possible permutations of how the NOUNS can interact with VERBS and ADJECTIVES are created in a table using queries. A frequency count is then done for        each permutation to find how many times an exact match is found. 

The NOUNS are labeled AGENTS and the VERBS and ADJECTIVES are labeled ACTION/STATUS.

The visual above shows the failure modes for slings. 

One is also able to see which parts are being damaged, broken or come loose the most. These are items that can be reconsidered for redesign or can be added to the daily pitstop tightening checklists. 

Freetext is difficult to work with, the best approach is to create failure codes but it is not impossible to  still get valuable data from freetext, it just costs you a bit of time and creativity.