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An essential part of the SHM validation effort is to check the presence and adequacy of the methods required to validate the correct functionality of each SHM task, which can be targeted at detecting structural faults. The ultimate proof of the correct functionality is validation evidence, e.g. crack detection evidence, observed during the operation of the aircraft. However, the occurrences of structural faults such as cracks are infrequent, and hence, years of flight tests might be required to collect validation evidence; small numbers of flights would be only sufficient to prove the system's “fitness for flight” and would be insufficient to prove “fitness for purpose”. Validation evidence can be collected during laboratory tests by inducing faults in structural specimens and examining the SHM detection capability.

A Distributed Engine Control Working Group (DECWG) consisting of the Department of Defense (DoD), the National Aeronautics and Space Administration (NASA)- Glenn Research Center (GRC) and industry has been formed to examine the current and future requirements of propulsion engine systems. The scope of this study will include an assessment of the paradigm shift from centralized engine control architecture to an architecture based on distributed control utilizing open system standards. Included will be a description of the work begun in the 1990's, which continues today, followed by the identification of the remaining technical challenges which present barriers to on-engine distributed control.

Quality has been the illustrious word of the 80s and 90s as we speak organizations are chasing quality problems through the engineering teams and into production. Taskforces of workers in white coats are being sent on to the production line to furiously check components, monitoring process capability in an attempt to improve product quality. Unfortunately it's only after several years of production that the first “real” data gets back to the engineering teams, when it is often too late to remove the causes of these quality problems. The organization is left kicking itself over the same old catch twenty-two situations, “If only the team knew this process data before they decided to engineer it like that!”