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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