[article]
| Titre : |
Data-driven corrosion prevention and control decisions for the usaf |
| Type de document : |
texte imprimé |
| Auteurs : |
Eric Herzberg, Auteur ; Charles A. Babish, Auteur ; Jeffrey K. Nusser, Auteur ; Darryl J. Stimson, Auteur |
| Année de publication : |
2018 |
| Article en page(s) : |
p. 32-41 |
| Note générale : |
Bibliogr. |
| Langues : |
Américain (ame) |
| Catégories : |
Aéronautique
Anticorrosion
Corrosion
Coût
Entretien et réparations
Revêtements protecteurs
|
| Index. décimale : |
667.9 Revêtements et enduits |
| Résumé : |
AF weapon systems accumulate about 50-to-65 percent of their total life-cycle costs during the O&S phase. Corrosion accounts for about 25 percent of this cost and could rise in the future due to the increased emphasis on the complex coating systems required by an increased emphasis on stealth aircraft. The AF has expanded its focus on corrosion prevention and control and the annual corrosion maintenance costs have leveled out at around $5.4 billion per year. However, to make significant and lasting improvements, the AF needs reliable maintenance data and analytical tools to effectively manage corrosion maintenance. This article proposes a suite of metrics and a decision-making process to make data-driven corrosion maintenance decisions for aircraft and other systems to increase the mission availability in the most cost-effective way possible.
The proposed process will enable stakeholders in the acquisition, sustainment, integrity programs and AF leadership communities to more accurately assess previous corrosion maintenance practices and prioritize future maintenance strategies. In sum, this approach will enable data-driven corrosion maintenance decisions.
Corrosion maintenance is simply a significant subset, albeit a large contributor, to aircraft maintenance cost and availability impacts. Consequently, the metrics and proposed decision-making process suggested here can be migrated to many other aircraft maintenance decisions and should be considered for adaption to a broader range of maintenance decisions from strategic levels at the AF headquarters, through MAJCOMs, and to the field, depot and contract maintainers. |
| Note de contenu : |
- Mission impact: this is war
- Corrosion maintenance metrics: meet in the middle
- Top-down: distillation approach to corrosion costs
- Bottom-up: stacking labor and cost data from individual maintenance records
- Scaling
- Next-generation corrosion analytics: data-driven maintenance decisions
- Proposed methodology
- Monitor maintenance data
- Identify problems and opportunities
- Analyze options
- Select and launch solutions
- Fig. 1 : Breakout of mission-available time and non-available time
- Fig. 2 : HC-130 corrosion at Patrick Air Force Base
- Fig. 3 : FY15 aircraft non-available hours (NAH) from corrosion maintenance. Corrosion maitenance consumes nearly 3 million hours - 18 percent of all NAH that systems are unavailable to perform their missions
- Fig. 4 : Corrosion costs the Air Force over $5 billion per year, nearly one quarter of all aerospace maintenance
- Fig. 5 : The inverse relationship between preventive and corrective maintenance. This national chart illustrates the maintainer's challenge of balancing preventive and corrective maintenance to yield the minimum corrosionmaintenance cost
- Fig. 6 : Top-down distillation to yield corrosion costs. To identify corrosioncosts, the total DoD budget is "distilled" by sequentially removing non-AF, non-aviation and non-maintenance costs until only corrosion-related maintenance costs remain. In reality, the crude oil distillation process removes the useful elements from the top. This example shows the most useful elements remaining at the bottom
- Fig. 7 : Aircraft NAH due to corrosion maintenance and corrosion portion of total NAH. These metrics have varied over time
- Fig. 8 : Corrosion maintenance cost and corrosion percent of total maintenance cost. Both have modestly decreased since 2012
- Fig. 9 : A model for the corrosion decision-making process
- Fig. 10 : An example of ametric showing maintenanc eactions that consume the most mission availability
- Fig. 11 : An example of a metric showing cost per day on maintenance actions that consume the most mission availability
- Fig. 12 : An example of a notional metric showing aircraft substystems that consume the most mission availability
- Fig. 13 : An example notional metric showing the cost perday of availability on aircraft subsystems that consume the most mission availability |
| Permalink : |
https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=31857 |
in JOURNAL OF PROTECTIVE COATINGS & LININGS (JPCL) > Vol. 35, N° 8 (08/2018) . - p. 32-41
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