electronics are still kept to a minimum and therefore
mechanical failures are predominant.
Wear mechanisms are also important in other sectors, such
as machine tools and lifts. However, in these two the
increased product complexities and the process characteristics
involving incorrect product usage increase the importance of
indefinite useful life, with random failure events difficult to
prevent.
The next stage would be to use failure modes to categorise
the data into quantifiable problems. This would include
simple analyses to determine what could go wrong, why
would the failure happen, and what would be the
consequences of each failure. The aim is to evaluate
processes for possible failures and to prevent them by
correcting the processes proactively rather than reacting to
adverse events after failures have occurred. However, this was
outside the scope of this initial investigation and requires indepth analyses of the data and data sources to be able to
confidently develop a set of failure modes. A detailed data
mining process would need to be developed in order to extract
valid, previously unknown, comprehensible information from
the organisations and individuals who supplied the data for
this study.