The return on investment for any maintenance organization is derived from a system's availability. Availability is a function of a system's mean time before failure (MTBF) and the mean time to repair (MTTR) a system once it has failed:
The MTTR translates directly into opportunity costs from the loss of availability. The longer it takes to repair a system the higher the maintenance costs inclusive of increased personnel to deal with failure frequencies and routine maintenance schedules.
Critical to lowering MTTR is the competency level of the
maintenance crew and the efficacy of their tools. If an organization has inherently
high attrition rates, such as a voluntary military, the competency levels of
their maintainers can vary widely. Learning curves are traditionally difficult
when dealing with complex systems. The time and effort to learn a system are
additional costs to the maintenance effort.
An ideal solution to improve competency levels are to
build tools that can improve learning asymptotically. Complex systems are
difficult to comprehend because of the enormous amounts of information
necessary to work with such systems. Human memory is inherently problematic and
information overload is a cognitive impediment, without information processing
tools dealing with information overload is impossible!
By transforming schematic diagrams into information that can be managed by information technology tools we can manage information overload. Atlas' tools turn static paper or raster diagrams into indexiable information that build information relationships that allow for intutitive human interaction to work with very complex systems, thereby lessening MTTR by improving compentency levels through shortenging the learning curve.
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