Page 37 - AAA JANUARY - FEBRUARY 2018 Online Magazine

COLUMN: MARK MARTIN
DIGITAL TWINS

The four technology developments set to
hit Commercial Aviation in 2018
espite longer-lasting aircraft, more durable
engines and innovations in maintenance
techniques, recent research has shown main-
Dtenance spending continues to increase. In
fact, airlines now spend more money on maintenance
than on fuel or crew. The need to cut maintenance,
repair and overhaul costs is a pressing issue for air-
lines, as is the need to keep assets operationally
available. So how can airlines keep aircraft in the air
while reducing maintenance costs? Here, Mark Martin,
Director, Commercial Aviation Product Line, Aviation &
Defense Business Unit, IFS, sets out four major tech-
nological developments that will help airlines meet Mark Martin
these challenges and produce major benefits across
the commercial aviation industry through 2018. Armed with this sort of data, engineers and MROs

1. Seeing Double can compare data gathered by sensors on the asset
to that of its digital twin, which can be put through the
Maintenance is one of the major contributors to air- same paces the engine experiences as it takes off,
craft operating costs. Flight delays and cancellations flies through different types of weather and under-
from unplanned maintenance cost airlines billions of goes regular wear and tear. If the two data sets don’t
dollars every year, not to mention the impact on cus- match up, then a request can be put in for the engine
tomer satisfaction. Because of this, the minimization to enter servicing. According to IDC, companies that
of operating costs and optimization of operational invest in digital twins will see a 30 percent improve-
availability continue to be top priorities for airlines. ment in cycle times of critical processes, including
Digital twins, a state-of-the-art method of monitoring maintenance. In 2018, expect to see more benefits
engines when in use, will help airlines achieve these as the technology matures.
aims. A digital twin refers to a virtual replica of a phys-
ical asset, like an aircraft engine, which can display
how the engine is running to engineers on the ground 2. AIl in the Sky
while the aircraft is still in the air. These can then be Artificial Intelligence (AI) is invading the skies. A SITA
linked to IT systems to help streamline and optimize report claims half of airlines surveyed will invest in
maintenance processes and operational availability. AI and cognitive computing in the next three years,
To make this happen, engineers compile thou- while a recent Aviation Digital Transformation survey
sands of data points specific to each asset during the saw 37 percent of respondents identify AI as a key
design and manufacturing phase of the engine. These area for investment. One of the biggest opportuni-
are then used to build a digital modal that tracks and ties for AI involves predictive maintenance. An Oliver
monitors an asset in real-time, providing essential Wyman report suggested that predictive analytics
information throughout an asset’s lifecycle such as can help optimize maintenance planning and capacity
engine temperature, pressure, and airflow rate. by reducing the need for routine maintenance.
By implementing digital twins and creating a virtual n Oliver Wyman report suggested that predictive
model of the asset, organizations can receive early analytics can help optimize maintenance planning
warnings, predictions and even a plan of action by and capacity by reducing the need for routine main-
simulating ‘what-if’ simulations based on weather, tenance and only triggering repairs when needed
performance, operations and other variables - helping - helping increase fleet availability by up to 35 percent
keep aircraft in service for longer. GE helped develop and reduce labour costs by 10 percent.
the world’s first digital twin for an airplane’s landing AI is helping bring this to reality by using data from
gear. Sensors were placed on typical failure points in-service aircraft to predict potential issues. These
on the asset, such as hydraulic pressure and brake algorithms are learning to predict delays and faults,
temperature, to provide real-time data and help pre- giving airlines, airports and MROs a better chance of
dict early malfunctions or diagnose the remaining avoiding them. The ability to correctly predict the
lifecycle of the landing gear. right moment o repair or replace a part is key to this

ASIAN AIRLINES & AEROSPACE January/February 2018 | 37