Asset management us air force

Asset management: What can utilities learn from the US Air Force?

The US Air Force has adopted a data-driven approach to asset management. Teradata tells us more about the approach and key learnings.
Published: Wed 21 Feb 2018

Utilities share a common challenge with other asset-intensive industries - the need to balance mission readiness with the availability of equipment against budget constraints.

The idea of achieving 100% availability of an asset fleet - whether generation equipment or distribution cabling and substations - by maintaining a sufficient spares inventory is not the reality for any industry working to a limited budget, explains Serigne Gaye, Asset Management Leader at Teradata International.

Finding ways around these constraints to ensure mission-readiness is possible however. By adopting a data-driven approach to asset management, asset intensive industries are getting the maximum availability of their equipment.

 

Teradata’s Serigne Gaye explains how there is no linear relation between increasing the budget for lifecycle costs and asset availability.

In an Engerati webinar ‘Asset management: What can utilities learn from other asset-intensive industries?’, Gaye explains how data and event analytics for assets has been a reality for other sectors including aeronautics.

Gaye says: "It may seem far from the utility industry but a very important case which we have been working on for years and delivering value to for years is the US Air Force (USAF) Materiel Command."

To give perspective, USAF is operating the largest airborne fleet in the world with Teradata supporting the asset management of thousands of aircraft and helicopters.

Gaye says the international analytics company provides a wide functional footprint for the USAF - from predictive maintenance to supply-chain analytics to transparency analytics.

Why this is relevant to the utility industry is because both share a similar remit.

“Applying a data-driven approach to asset management for the military is really the definite proof that is it possible to do it absolutely elsewhere. This is an organisation that is very much asset-intensive on one side and on another side has mission-ready challenges.”

US Air Force Materiel Command manages more aircraft than the whole of the global commercial airlines industry.

Data-driven approach - maintenance

What a data-first approach to asset performance means in the USAF context is covering end-to-end maintenance, repair and overall supply chain.

Analytics is controlling every aspect of that supply chain relating to mission-readiness for the whole fleet and within high-budget constraints.

Gaye says: “At USAF, we are doing predictive maintenance, looking closely at combat aircraft, harvesting data from sub systems that compose that aircraft and putting that subsystem under surveillance and scheduling maintenance activity before the subsystem breaks.”

Asset-management, however, is not only about doing predictive maintenance, says Gaye “it’s much more than that”.

Data analytics can support a complex problem such as deciding on the compatibility and configuration management between spare parts and aircraft configuration.

“Data analytics will determine if it is possible to mount a given part on a given aircraft and still have airworthiness ie. the right to fly that aircraft,” says Gaye.

Teradata is also working with USAF to optimise the spare parts inventory. “Our data-driven approach determines which parts to order and in which quantity in order to have a given level of availability and still respecting the budgetary constraints.”

Gaye says “under the umbrella of data analytics-driven asset management,” USAF Materiel Command has oversight over its maintenance, repair and supply chain

Asset-intensive industries - analytics use

When it comes to applying this asset-data knowledge to other sectors, Gaye explains “this knowledge from the USAF and the military has been sharpened at Caterpillar.

Teradata is working with the heavy truck manufacturer and operator to discover a path-to-failure.

“What has been designed by engineers is not always what will happen in the field. We can draw on data from sensors embedded within the trucks and sub-systems in order to build a path-to-failure and understand how different parameters will combine to produce a measurable event.”   

He concludes: “In fact, any industry that needs repair and maintenance efficiency, lifecycle costing, cost-breakdown structure will benefit from the data-driven approach to asset management developed for USAF.”

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