Fitness for Purpose, Censoring, and the Discipline of Turning Reliability Data into Reliability Decisions
A reliability engineer who has worked in this field for any length of time has been handed a stack of data and asked to make sense of it. The stack is rarely fit for the question that motivates the engagement. The collection system was usually designed for a different purpose by people in a different function; the records are incomplete in ways that distort the underlying distribution, and the volume of data is sometimes large enough to disguise the absence of useful information. This paper sets out ten principles for working with reliability data well: starting from fitness for purpose, working through the structural problems of censoring and missing renewals, addressing the volume problem with reliability performance indexing, and ending with the most important and most neglected of the ten, talking to the people who collect the data so that the next dataset is better than the last one. The principles are drawn from a Speaking of Reliability conversation between Philip Sage and Fred Schenkelberg and have been translated here into a structured engineering doctrine in the TMG voice.