Accession Number : AD1041066


Title :   How Accurately do Leading and Lagging Indictors Predict F-16 Aircraft Availability (AA)


Descriptive Note : Technical Report


Corporate Author : AIR COMMAND AND STAFF COLLEGE, AIR UNIVERSITY MAXWELL AFB United States


Personal Author(s) : Brauer,Craig S


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1041066.pdf


Report Date : 01 Aug 2016


Pagination or Media Count : 51


Abstract : How accurately do leading and lagging indicators predict F-16 aircraft availability (AA)?In todays environment of doing more with less, aging aircraft and shrinking budgets, it is imperative for maintenance leaders to use all tools available to them to improve the amount of aircraft available for operations. One of the leading ways to gauge a units effectiveness was and still is the mission capable (MC) rate. This rate is a lagging indicator of how a unit is performing. This metric is very valuable to measure how a unit is doing, but it focuses more on the tactical level of operations. Emphasis has switched to how that unit is fitting into the overall AF mission or the operational level of doing business. How many aircraft a unit has available is the metric for that emphasis. There has been a major shift from using MC to using Aircraft Availability (AA) to gauge how the unit is performing. This research project used a mixed method approach to evaluating the data compiled to test the thesis that using leading and lagging indicators is the most accurate way to measure AA for the F-16 aircraft. Although the concept of AA has been around for quite a while, it is only recently that it is now the standard on how leadership appraises their fleets. The ability to predict AA of a fleet has always been a goal of leadership and is now more important than ever with budget cuts that affect the way the AF has to do business. The use of lagging indicators to predict and leading indicators to monitor these predictions is critical to the AF being ready to meet all commitments and taskings. Data shows that this method is accurate to 99.92 percent for F-16 AA prediction.


Descriptors :   indicators , aircrafts , maintenance , accuracy , system software , life cycle management , availability , logistics support


Subject Categories : Aircraft


Distribution Statement : APPROVED FOR PUBLIC RELEASE