The document discusses predictive maintenance and the Internet of Things (IoT) in the context of aircraft maintenance, repair, and operations. It describes how predictive maintenance goes beyond traditional approaches to also predict component failures before they occur. This allows time to prepare and prevents aircraft from being taken out of service unnecessarily. Dynamic diagnostics are also discussed, which can now be proactive by analyzing real-time sensor data using reasoning engines. Significant amounts of operational data from aircraft need to be managed. Original equipment manufacturers are developing solutions for their own aircraft, but an open, interoperable approach across the industry is needed to realize the full benefits.

1. White Papers: IFS; Predikto Case Studies: ADAC Luftfahrt Technik; FL Technics
PLUS… How I see IT, News, Upcoming and Past Webinars, MRO Software Directory
V4.5 • OCTOBER/NOVEMBER 2015
PLANNING A SUCCESSFUL
MRO IT IMPLEMENTATION
ADAC LuftfahrtTechnik makes sure change fits the business
BIG DATA &THE
INTERNET OF THINGS
Using data and connectivity
to better manage aircraft
MANAGING
MRO IT CHANGE
FL Technics has ensured that
everybody supports new ideas

2. AircraftIT MRO is published bi-monthly and is an affiliate of Aircraft Commerce and part of the AviationNextGen Ltd group. The entire contents within this
publication © Copyright 2015 AviationNextGen Ltd an independent publication and not affiliated with any of the IT vendors or suppliers. Content may not
be reproduced without the strict written agreement of the publisher. The views and opinions expressed in this publication are the views of the authors and
do not necessarily reflect the views or policies of their companies or of the publisher. The publisher does not guarantee the source, originality, accuracy,
completeness or reliability of any statement, information, data, finding, interpretation, advice, opinion, or view presented.
AircraftIT MRO
Publisher/Editor: Ed Haskey
E-mail: ed.haskey@aircraftit.com
Telephone: +44 1273 454 235
Website: www.aircraftIT.com
Industry 4.0 is all about the digital world of work;
something with which MRO professionals are
increasingly familiar
‘Industry 4.0’ is the short-hand term for something that will soon be entering all our lives,
if it hasn’t already done so. It’s the fourth industrial revolution and for people in all walks
of life, represents the ultimate conquest of the world of work by the forces of IT. It is the
shift of work to a wholly digital basis with all the advantages that will bring. Instead of
technology simply speeding up processes that were previously completed by people,
it is now making possible processes that could not have been considered before. For
instance, predictive maintenance is set to significantly reduce the incidences of aircraft
failure… thus increasing reliability and safety as well as the passenger experience.
But, whatever IT developments there might be, their implementation is as important
as any technical attributes. Knowing what to do with the system, how to apply it
effectively and what to apply it to as well as what to get out of it is just as important as
the system itself. Also important is keeping the team onside as the changes come into force: change management
is one of the most important management skills, especially when a sector has to manage as much change as MRO
and MRO IT.
This issue includes a further exploration of the Internet of Things and what it can offer to commercial aviation,
including predictive maintenance and aircraft health management. There’s also an article about how to ensure that
you select the right solution for your business and then implement it in the most beneficial manner. As well as the
Internet of Things we also look at Big Data, a topic of increasing importance as next generation aircraft enter service,
generating terabytes of information about themselves and their environment from every flight. Finally, we look at a
novel and successful way in which one business introduced to its workforce the idea of change through asking them
what they wanted; I said it was a novel idea and it shows some careful thought about how to gain acceptance for
change. Also, there’s a preview of the Airline & Aerospace MRO and Operations IT Conference – APAC – Bangkok,
Thailand, 28th & 29th October 2015.
On top of all that is the usual overview of news and information affecting your sector plus upcoming Aircraft IT live
demonstration webinars and past webinars; not forgetting, of course, how Paul Saunders sees IT and, in this issue, 3D
printing which is set to revolutionize so many industrial processes.
Aircraft IT MRO: like Industry 4.0, it reaches every corner in your world of work.
Ed Haskey
04 LATEST NEWS AND TECHNOLOGY
UPDATES
Keeping up with the latest developments in your
professional world can be a challenge. But simply go to
www.aircraftit.com/MRO or here in the Aircraft IT MRO
e-journal to keep up to date with the latest developments.
16 CASE STUDY
LESS IS MORE’ AT FL TECHNICS
Ramunas Paskevicius, Head of IT unit, FL Technics
Change management is often a challenge but what about
getting people used to change by asking them to initiate
small changes themselves? Here is a case where that way
of thinking has already paid dividends.
20 CASE STUDY
ROTARY WING MRO IT
Jan Ketelsen, Manager Maintenance Planning,
ADAC Luftfahrt Technik GmbH
ADAC LuftfahrtTechnik’s success story in selecting,
implementing and using their MRO IT system has taught
them that planning any such move properly ensures that
changes fit what the business really needs.
24 EVENT PREVIEW
AIRLINE & AEROSPACE MRO AND
OPERATIONS IT CONFERENCE – APAC
Bangkok, Thailand, 28th & 29th October 2015
The Airline & Aerospace MRO and Operations IT Conference
– APAC, returns to Bangkok for 2015 with: 40+Vendors,
keynote presentations, case studies, interactive workshop
sessions andVendor showcase sessions.
27 COLUMN: HOW I SEE IT
Paul Saunders: 3D or not 3D? That is the question.
3D technology has potential for design, maintenance
and parts manufacture in MRO but there are hurdles to
overcome before the technology becomes everyday reality.
28 WHITE PAPER
THE INTERNET OF FLYING
THINGS PART 2
Michael Wm. Denis
The Internet ofThings improves MRO processes like
predictive maintenance, diagnostics, prognostics and
asset management; plus enhances flight ops, enables
servitization and supporst more efficient business models.
34 ON-DEMAND WEBINARS: ACCESSIBLE
KNOWLEDGE FOR PEOPLE WHO
NEED TO KNOW
View On-Demand video recordings of Past Live MRO
Software DemonstrationWebinars. See full information
and view On-Demand videos of past Live MRO Software
Demonstrations, including: Boeing,TRAX and Commsoft.
38 WHITE PAPER
USING BIG DATA TO SCHEDULE
UNPLANNED MAINTENANCE…
STREAMLINING THE A&D SUPPORT
CHAIN
Brendan Viggers, Product & Sales Support for the
IFS A&D Centre of Excellence
Big data is here inasmuch as huge volumes of information
are being generated by myriad systems and devices: the
trick will be to determine how to use that data to better
inform decisions and processes.
41 VENDOR JOB CARD: WHAT DOES
ADSOFTWARE DO FOR CLIENTS?
In the latest of our Q&A pieces, Frédéric Ulrich, Founder and
CEO of ADSoftware, completes his‘Vendor Job Card’.
42 MRO SOFTWARE DIRECTORY
A detailed look at the world’s leading MRO IT systems.
V4.5 • OCTOBER/NOVEMBER 2015
Welcome…
CLICK HERE: Send your feedback and suggestions to AircraftIT MRO
CLICK HERE: Subscribe for free
Copy Editor/Contributor: John Hancock
E-mail: john@aircraftit.com
Magazine Production: Dean Cook
E-mail: deancook@magazineproduction.com

3. The Internet of Flying Things: Part 2
In this second of two articles, Michael Wm. Denis presents valuable considerations for Internet of Things
initiatives and how companies can profitably cash the check of predictive maintenance
28 | WHITE PAPER: INTERNET OF FLYING THINGS: MICHAEL WM. DENIS | AIRCRAFT IT MRO | OCTOBER/NOVEMBER 2015

4. OCTOBER/NOVEMBER 2015 | AIRCRAFT IT MRO | WHITE PAPER: INTERNET OF FLYING THINGS: MICHAEL WM. DENIS | 29
W
ALKING ABOARD DELTA’S new A350-900
XWB, you are impressed with its lighting, 1-2-
1 herringbone layout and, of course, the plush
lie-flat seats. It definitely appears your flight to FRA
and onward to the Aircraft Commerce MRO/OPS IT
2020 conference in Darmstadt will be quite pleasurable.
Snuggling into the wide birth and pitch of the Zodiac
BusinessElite seats, the amenities are immediately
apparent, starting with the Thales IFE, USB ports, power
chargers and GoGo Ku-band satellite Wi-Fi that covers
the entire international flight.
As the aircraft revs its engines at the end of the
runway and then shudders slightly when the pilot
releases the brakes, you momentarily flash back five
years, remembering the engine fire on BA 2276 at
LAS McCarran International Airport. And it was
during another aviation maintenance conference that
you sat next to the Qantas Director of Maintenance
(DOM) as his mobile phone kept ringing during your
joint presentation, only to later find out that A380
QF32 had suffered an in-flight uncontained engine
failure and was limping back to SIN Singapore
Changi Airport.
But today’s flight will be uneventful, knowing that
Delta had implemented predictive maintenance,
dynamic diagnostics, prognostics and health
management systems in 2016 and such events, as
rare as they were before, had become non-existent.
After a wonderful meal, wine and movie, you pop
out your laptop to put the finishing touches on your
presentation, The Internet of Flying Things — Lessons
Learned Five Years Later.
While safety of flight and reliability are always key
success factors within the aviation community, it was
financial return that motivated most airlines and OEMs
to invest in predictive maintenance and prognostic
health management. William T. Greene, Vice President,
Technical Operations Finance and Strategic Planning
at American Airlines, always used to ask a simple
question when someone brought him a bright idea,
“How do I cash that check?”
The Internet of Flying Things, that is how.
PREDICTIVE MAINTENANCE
This article picks up from where part 1 left off;
understanding what the Internet of Things (IoT) is,
how we go about creating the potential and how we
deliver tangible real value.
There are plenty of everyday manifestations of the
IoT around us already. A SmartHealth watch senses our
vital signs, interprets our sleeping pattern and current
health in order to determine or prescribe
when we should wake up, decides which of a
plethora of home appliances to turn on based upon
one’s personal schedule, and then responds by
communicating to and controlling a SmartAlarm,
SmartLighting, SmartHVAC, and maybe a
SmartToaster. Of course, it might be apposite to ask,
do we really need a ‘Smart Toaster?’
In the Google Nest example (see previous article),
their SmartHVAC doesn’t merely provide remote
control and static remote programing of temperature
set at specific times. Via geolocation sensing, Nest
knows when people come and go at the house, what
the weather is at the home’s specific location now and
in the future and over time, via machine learning,
develops personalized behavioral patterns. This gives
Nest the ability to optimize a home’s temperature
and humidity specific to the user and specific to the
constantly changing environment. With the addition
of smart remote control dampers, Nest can easily
reduce energy costs by directing heat or cool air to
specific rooms that residents are actually in while
preparing other rooms for future use, say a bedroom
just in time for sleep.
Nearer to home for MRO is predictive maintenance
(PdM) and it’s much more than predicting component
failure. PdM builds upon RCM (reliability centered
maintenance), CBM (condition based maintenance)
and an operator’s current MSG-3 maintenance
program from the ATA’s maintenance steering group
(MSG) tailored for each specific tail or rotable. PdM is
a cyclical group of capabilities that enables continuous
improvement in reliability, quality, safety, asset
performance and total cost of operations.
“Withrespecttoengineeringfunctionalspecifications,mostcomponents,assemblies,
appliancesandsystemshavemultiplefunctionalattributesandevenmorefault
andfailuremodes.Failureofacomponentiswhenatleastonecriticalattributeis
continuouslyoperatingoutsideofanengineeringform,fitorfunctionaltolerance
specification.”
INTERACTIVE Click here for full product details
C
M
J
CM
MJ
CJ
CMJ
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2moroAnnoncePresse1112.pdf 11/01/12 16:12:56

5. 30 | WHITE PAPER: INTERNET OF FLYING THINGS: MICHAEL WM. DENIS | AIRCRAFT IT MRO | OCTOBER/NOVEMBER 2015
Predictive maintenance augments traditional maintenance methodologies
(RCM, CBM…) and the capabilities and processes that everyone performs
today. What is fundamentally different is predictive maintenance gives
operators time to prepare actionable courses of action.
Normally we detect degradation from routine inspections or continuous
condition monitoring until a component eventually fails an engineering
specification — form, fit or function. With respect to engineering
functional specifications, most components, assemblies, appliances and
systems have multiple functional attributes and even more fault and failure
modes. Failure of a component is when at least one critical attribute is
continuously operating outside of an engineering form, fit or functional
tolerance specification.
In prediction, one can predict engineering functional failure or non-
failure, also known as false positives and the prime reason for no fault
found (NFF).
The first of these is pretty obvious. A sensor or inspection indicates at
least one critical engineering attribute is outside of a tolerance level and it
truly is. The converse, non-failure, is when a sensor or inspection indicates
an out of tolerance condition but it actually is not. This is called a false
positive or Type I error. There is also what is known as a false negative or a
Type II error.
So prediction identifies that a component is headed down its RCM P-F
(interval between Potential failure and Functional failure) curve at some
point in time before failure, given some level of predictive accuracy or it
predicts and prevents no fault found. The bottom line value proposition
of prediction is delivered in time. In the diagram, it is the time to respond
prior to failure or non-failure without taking a revenue generating asset out
of revenue generating service.
DYNAMIC DIAGNOSTICS
Traditionally, diagnostics has been considered a lagging or reactive
capability — that is; engineering form, fit or function is already degraded,
fault mode codes are being sensed or full failure has occurred. While
in many cases this maturity level of diagnostics is still commonplace,
especially when using static TSM (troubleshooting manual) or FIM (fault
isolation manual) manuals, in the context of predictive maintenance and
predictive analytics, diagnostics is becoming proactive. Customizable
diagnostic reasoning engines that operate on a database of known
equipment issues (i.e. a fault isolation) can capture all of the symptoms,
causes and solutions for every known failure mode for a specific type,
model, series or even individual piece of equipment. By dynamically
generating decision logic, these proactive diagnostic systems rapidly
identify the root causes of problems to guide users to the right prescriptive
and corrective actions.
New generation commercial aircraft create up to 1 terabyte of operational
data per flight from the plethora of sensors on board. Additionally,
they have become software driven devices and there is an unintended
consequence of hardware that doesn’t function correctly without the
correct software, that being, diagnostics becomes unmanageable in a world
of static CMS (content management system) enabled TSM/FIMs.
Jeff Immelt, CEO at General Electric succinctly sums up the new world
order, “If you went to bed last night as an industrial company, you’re going
to wake up this morning as a software and analytics company. The notion
that there’s a huge separation between the industrial world and the world of
digitization, analytics and software is over.”
And Mr. Immelt’s observation is at the center of much of the increasing
complexity in diagnosing faults in aircraft systems and components, the
constantly changing hardware, software configurations and the static
nature of paper or even electronic content management systems.
The lack of predictive maintenance and advanced analytics capabilities
adversely impacts fleet managers’, line mechanics’ and AOG (aircraft on
ground) desk managers’ ability to support D-15 technical dispatch rate
punctuality.
At the April MRO and OPS IT conference in Miami, Airbus presented
their long range plan to incorporate predictive maintenance and advanced
diagnostics capabilities into their OEM (original equipment manufacturer)
specific solutions and we can be assured that Boeing, Bombardier, Embraer,
GE, Pratt & Whitney and others will also build OEM asset specific tools.
But even if an airline is a single fleet operator, unless they also perform all
of their maintenance, repair and overhauls in house — I don’t know any
who do — then OEM specific tools are no real enterprise solution. And of
course the OEM-MRO ecosystem requires open standard interoperability
across Information and Operations technologies and architecture for the
entire industry to realize the value of everyone’s investments, something
that mere data standards will not solve.
OEN AGNOSTICE PREDICTIVE AIRCRAFT
HEALTH MANAGEMENT ARCHITECTURE
FAULT ISOLATION PROBLEM = MULTIPLE CONSTANTLY CHANGING
HARDWARE/SOFTWARE CONFIGURATIONS
CLOSED LOOP SLM: FROM SENSE TO PREDICT TO DAIGNOSE TO REPOND

6. OCTOBER/NOVEMBER 2015 | AIRCRAFT IT MRO | WHITE PAPER: INTERNET OF FLYING THINGS: MICHAEL WM. DENIS | 31
IoT OPERATIONAL AND INFORMATIONAL ARCHITECTURES
Predictive maintenance must be implemented in actual airlines’ current
and future technology systems. IoT is commonly described as combining
Information Technology (IT) and Operational Technology (OT). IT
is exemplified by ERP (enterprise resource planning), SCM (supply
chain management), CMS and MRO systems whereas OT includes the
on board Central Maintenance Computer (CMC), engine control and
avionics systems and even near board systems like diagnostics or health
management systems. An aviation OT architecture might appear like the
one below:
This data is being processed in-flight and post-flight, combined with
human actions and content, and then combined with IT in order to
predict, diagnose and prognosticate who should do what, where and
when in order to optimize asset utilization, labor productivity and supply
effectiveness. This requires a combined OT and IT integration. Because
authoritative data and transactions move from an aerospace OEM’s
Product Lifecycle Management (PLM) system through manufacturing
execution (MES) to an operator’s Service Lifecycle Management (SLM)
system, the ecosystem IT architecture looks like this:
To actually realize value from PdM capabilities, IT and OT systems
will need to be integrated and matured. Doing that starts with an
understanding of the state of these systems today and a plan on where to
go moving forward. And because IoT is an ecosystem set of capabilities,
they cannot be integrated or matured in a vacuum. If your aircraft or
engine or component OEMs don’t enable OT sensing or if your MRO
vendors don’t improve their MRO, CMS, digital and mobility capabilities,
then building the best internal IT and OT will mean realizing less value
from your investment thus increasing the costs for everyone in the aviation
ecosystem.
SERVITIZATION: PERFORMANCE BASED BUSINESS MODELS
Probably the most disruptive element of IoT is how it enables servitization
of ‘products’ or ‘devices’ and thus totally changes a company’s business
models. It is interesting to note that, in the general media, the most often
cited example of how IoT fundamentally changes a company’s business
model via servitization is Rolls-Royce. We in aviation are very familiar
with ‘Power by the Hour’ and how it bundles a ‘product’ or ‘device’
funding, purchase price, warranty, maintenance, service parts, etc… and
denominates the price paid in what is actually being consumed — thrust.
This is what is meant by ‘servitizing’ a ‘product’.
In IT this is commonly referred to as Software-as-a-Service (SaaS),
Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS).
Salesforce is a prime example of both a PaaS, where any software vendor
can develop and host their solution, while also being a SaaS for their own
CRM solution. And in order to optimize revenue and profits and market
share, Salesforce PaaS hosts competitor’s CRM SaaS solutions. This is
what is known as coopetition or the combination of cooperation and
competition.
The greatest challenges for companies from this point on are not
technological — transport protocols, data standards, security, connectivity,
etc.; rather, they are centered on realigning their thinking, strategy and
business models for servitization, a future that has already arrived.
There is no such thing as a product. Products only exist in the minds
of the inept. Products only exist for the ‘spoilable’ service they deliver.
Services and Service Lifecycle Management is where the check is cashed.
Again, it’s much easier for us in aviation to understand these principals
since an aircraft is really only a factory for creating available seat miles
(ASM) for pax and available ton kilometers (ATK) for freight. Aviation
metrics are all denominated in RASM (revenue per available seat mile),
CASM (cost per available seat mile), LF (load factor), RPM (revenue
passenger mile) and Yield.
Back to our Google Nest example. Even Honeywell Home Automation
would probably, privately admit they were asleep at the switch (pun
very much intended); arguably they are still asleep. While Honeywell
has developed a similar ‘device’ or ‘product’ to Nest, that includes basic
remote programming and control of a home’s HVAC, Nest is partnering
with electricity and natural gas utilities and heating and air conditioning
manufacturers to build a total home energy management offering,
servitizing not only their own devices but HVAC’s devices too.
As many airlines have now experienced as they have brought new
generation aircraft on board, OEMs are placing onerous constraints on
their use of home grown and, or third party technologies. The battle
over Operational Data and content has gotten worse. Counter to IT and
OT trends in most other industries, with few exceptions, aerospace is
becoming more OEM proprietary, non-standard, non-open.
“AttheAprilMROandOPSITconferenceinMiami,Airbuspresentedtheirlongrangeplantoincorporatepredictive
maintenanceandadvanceddiagnosticscapabilitiesintotheirOEM(originalequipmentmanufacturer)specific
solutionsandwecanbeassuredthatBoeing,Bombardier,Embraer,GE,Pratt&Whitneyandotherswillalsobuild
OEMassetspecifictools..“
“IfyouraircraftorengineorcomponentOEMsdon’tenableOTsensingorifyourMROvendorsdon’timprovetheir
MRO,CMS,digitalandmobilitycapabilities,thenbuildingthebestinternalITandOTwillmeanrealizinglessvalue
fromyourinvestmentthusincreasingthecostsforeveryoneintheaviationecosystem.”
AVIATION SERVICE LIFECYCLE MANAGEMENT OPERATIONS
AVIATION TOTAL LIFECYCLE INFORMATION ARCHITECTURE

7. 32 | WHITE PAPER: INTERNET OF FLYING THINGS: MICHAEL WM. DENIS | AIRCRAFT IT MRO | OCTOBER/NOVEMBER 2015
GE invested $105M USD in Pivotal, a provider
of cloud IaaS and analytics services. After such an
investment, most companies would consider Pivotal
a strategic competitive asset and try to lock out
competitors. To the contrary, GE has opened their
Predix platform to the world. Coopetition at its finest.
MONEYBALL, CHANGING AN UNFAIR GAME
If you haven’t read Michael Lewis’ book, Moneŷball:
The Art of Winning an Unfair Game, or at least seen
the movie, I highly recommend it. It’s for anyone who
loves baseball or operations research or just a good
story about people and family.
Baseball is fundamentally unfair because of the
revenue distribution and ability for big-market teams
— the New York Yankees, Boston Red Sox and Chicago
Cubs — to generate revenue that allows them to pay
more for their players. That makes it nearly impossible
for small-market teams such as the Kansas City Royals,
Milwaukee Brewers and the Oakland Athletics (A’s)
to compete. Of course you can say the same thing
about business. Some are global multi-billion dollar
behemoths with more free cash flow and capital than
they know what to do with; and then the rest of us are
in the small to medium enterprise domain.
Moneŷball examines how Billy Beane, the general
manager of the Oakland A’s, used unconventional
data and statistics to smartly and affordably assemble
a competitive small-market baseball team in the early
2000s. Granted, there is nothing extraordinary about
using statistics to win baseball games… or business for
that matter. Every kid who collected baseball cards for
the past 100 years knows the runs batted in (RBI) or
earned run average (ERA) of their favorite players.
Statistician Bill James, a pioneer of sabermetics (the
basis for Beane’s Moneŷball approach), took baseball
statistical analysis and prediction to the next level when
he began publishing books about it in 1970s and 80s.
The revolutionary idea that James developed and Beane
discovered was that the traditional metrics used by
general managers, scouts and teams to forecast player
value, for decades, did not actually result in team wins.
For example, instead of ERA, Moneŷball uses
Peripheral ERA (PERA), the ‘expected’ ERA taking into
account park adjusted hits, walks, strike outs and home
runs. Instead of RBIs, James developed Runs Created
(RC) which forecasts the number of runs a hitter is
‘expected’ to contribute to a specific team taking into
account the parks that team plays in.
Billy Bean explained the reason for seeking a new
way of prediction; “We had to look for new knowledge,
we had to question everything. We found great
inefficiencies in how everyone was evaluating players.”
Beane broke the biases of his scouting staff, who had
always done things their way, by ignoring qualitative
opinions like age, appearance, personality and playing
style as well as traditional quantitative metrics like
batting average and RBIs and instead relied on often
overlooked statistics like on base percentage and
slugging percentage — numbers that were actually
better indicators of a player’s ability to create runs.
Because creating more runs than the competition wins
games.
As he explained it, “It’s really about information and
it’s about making probabilistic decisions — we couldn’t
afford to invest something and not get a return. We
couldn’t take risk, we had to look at things like an
actuary looks at things and understand future decision
risk. This is really about getting the most information
to make good decisions. We were trying to rob some of
the things that were going on in Wall Street and apply
them to baseball.”
The strategy worked! The A’s reached the playoffs in
2002 and 2003 and were competitive with the New
York Yankees, a team that spent $80+ million more on
its roster’s payroll. With this success, the Moneŷball
phenomenon transformed baseball…and also the
world beyond.
Moneŷball is about reducing risk while increasing
the expected value of actionable decisions through
quantitative and predictive analysis of a lot of disparate
data, more commonly referred to as ‘big data’.
Enter 100 billion sensors, 50 billion connected
devices, a yottabyte of data and $14.4 trillion in
economic impact.
The consumer and industrial Internet of Things
are pontificated to change how businesses deliver
everything. IoT is ushering in the biggest and most
disparate increase in data seen since the invention
of the internet, leading some to say ‘big data’ is the
equivalent of ‘oil’ — a currency unto itself.
But you don’t run cars or factories or power plants
on oil. Just like oil, big data must be processed into
fuel for use; sensor and transactional data needs to be
processed and transformed into actionable knowledge
before systems and, or people can make decisions and
respond in a timely manner.
When Rick Wysong was VP Engineering, Strategy &
Planning at United Airlines, he once told me UA was
filling Teradata data bases up with ‘tons’ of data and
that, maybe six months after the fact, his engineers
would figure out what they should have done six
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8. OCTOBER/NOVEMBER 2015 | AIRCRAFT IT MRO | WHITE PAPER: INTERNET OF FLYING THINGS: MICHAEL WM. DENIS | 33
MICHAEL WM. DENIS
Michael Wm. Denis
is a renowned
author, speaker and
independent consultant
providing strategy,
business model, organization,
marketing, sales, operations and
technology advisory services
to manufacturers, operators,
maintainers and technology vendors
focused on optimizing the service
lifecycle of complex capital assets.
Among other clients, Michael
is advising several predictive
maintenance solutions vendors’
strategy and business development
in the aerospace, aviation and
defence markets.
www.slm.aero
CASEBANK
CaseBank Technologies is a pioneer
and leader in delivering diagnostic
solutions for complex capital assets
that improve first time fix rates,
labour productivity and equipment
reliability. CaseBank’s Spotlight®,
ChronicX® and Diagnostics Data
Analyser™ incorporate actual
feedback from field service
technicians to accelerate future
corrective actions. CaseBank
guides the fault isolation processes
and procedures to optimize the
efficiency and consistency of
product support. Its solutions are
used by maintenance organizations
in a variety of industries, including
aviation, defence, automotive, rail,
industrial equipment, and high tech
electronics.
INTERACTIVE Give us your opinion
Click here to post your comment
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months earlier. Rick didn’t need more data, he needed better faster decision
capabilities.
Accelerating sense and respond and improving accuracy and precision
lies at the heart of value creation and value realization in IoT and PdM.
Which brings us back to Will Greene; “How do I cash that check?” That
simple question anchors every successful CxO’s decision making process.
Realizing the value of industrial IoT begins with accurate and precise
decision-making focused on the right criteria, outputs and outcomes
throughout an organization. That’s the Moneŷball effect. So what does
Moneŷball teach us about cashing the check in IoT?
• It teaches us that what is termed the Internet of Things is an equalizer for
small to medium sized companies to compete and collaborate with ‘the
big guys’;
• That there is sedentary inertia within organizations not to change thus
requiring visionary and assertive leadership to overcome the innovator’s
dilemma;
• That IoT applies to both planning (buying the right equipment, players,
partners) and execution (operations of people, plant, equipment,
marketing, sales);
• That merely connecting edge devices does not, in and of itself, realize
value;
• That the ability to sense and gather data (big, small, or otherwise) creates
potential value that must be realized across the Product and Service
Lifecycles in addition to Customer Experience;
• That companies investing in IoT need to look at asset and operations
performance levers and how sensing, monitoring, controlling,
predicting, diagnosing, prescription, prognosis and autonomics improve
decision making to change outcomes; and…
• That predictive analytics (predictive maintenance in industrial markets)
delivers the lead-time required to respond to asset, operations and
customer events in order to optimize return on assets, return on
operations and return on investments.
SO, WHAT IS THE INTERNET OF THINGS?
The Internet of Things is neither about the Internet nor about Things; it is
about creating outcomes (baseball runs and wins or safe on-time departure
of aircraft).
It’s about connecting edge devices that sense conditions to systems that
monitor, analyze and process stochastic events, automatically gathered by
both machines and humans, to create value from autonomic manipulation
of data into knowledge for the purpose of making timely actionable
decisions in order to realize value for consumers of spoilable services.
“Justlikeoil,bigdatamustbeprocessedintofuel
foruse;sensorandtransactionaldataneedstobe
processedandtransformedintoactionableknowledge
beforesystemsand,orpeoplecanmakedecisionsand
respondinatimelymanner.”
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9. 38 | WHITE PAPER: IFS | AIRCRAFT IT MRO | OCTOBER/NOVEMBER 2015
Using big data to schedule unplanned maintenance…
streamlining the A&D support chain
BrendanViggers, Product & Sales Support for the IFS A&D Centre of Excellence, looks at how the A&D industry is using big data to revolutionise unscheduled maintenance

10. OCTOBER/NOVEMBER 2015 | AIRCRAFT IT MRO | WHITE PAPER: IFS | 39
I
T IS ESTIMATED that from each and every Boeing
787 flight, 500GB of data is collected, and everything
from the cabin pressure to the pressure of the tires is
recorded. But what happens to that massively growing
amount of ‘big data’? The tangible benefits of processing
and applying big data in the Aerospace and Defense
(A&D) industry, in particular for the military, are only
just being seen.
WHAT IS BIG DATA?
Big data, as a concept, has been around for a long
time but is now coming of age due to our ability to
know what to do with it. The term ‘big data’ is used
to describe a massive volume of both structured and
unstructured data from an equally varied set of sources,
so large that it’s difficult to process using traditional
database and software techniques. Big data is usually
described in a five step model, data — filter — context
— process — analysis, but, more importantly, has the
potential to help companies improve operations and
make faster, more intelligent decisions if processed and
applied correctly: in turn, allowing A&D organizations
to realize a number of genuine benefits.
WE HAVE BIG DATA BUT NO BIG PICTURE
With a wider view, analysis of these data sets can find
new correlations to spot business trends. These data
sets continually grow in size in part because they are
increasingly being gathered by numerous information-
sensing mobile devices.
The problem to date has not come from big data itself,
it has come through the interpretation of that data —
we simply do not know which patterns are relevant
and which aren’t, or how to turn them into a realizable
benefit. Perhaps the most well-known example of
the use of big data is Google. Through reading and
indexing huge amounts of information across the
Internet, Google is able to compare against your search
terms and, from that comparison, determine what you
are looking for. But look past the first page of results
and you start to see the real problem; because what we
see is mostly irrelevant.
So far, this is precisely what we have seen from big
data in the A&D industry. There is a massive wave
of valuable and untapped data collected from land,
sea and air assets, but the industry has to decide what
best to do with it. We have the big data, but where is
the big picture?
HOW THIS AFFECTS A&D — REMOVING THE
NOISE AND INFORMING ACTIONS
With all this data, it is important to be able to filter out
which events are causing ‘noise’ and therefore making it
difficult to make decisions, in order to see the wood from
the trees. If we take the Boeing 787 for example, what
do you do with 500GB of data which is accumulated
from every flight? An airline’s or operator’s systems and
applications have to be smart enough to filter out the
information and present users with a set of data which
they can act upon. It could well be that 499.9GB of that
data is just standard flight information from multiple
devices and the 0.1GB remaining is actually data that you
should apply. IFS Labs, the research unit within IFS R&D
which explores new areas of application functionality
and provides a testing ground for new initiatives and
‘proof of concept’ projects not yet proven for large scale
deployment, has already made great strides in helping
to define which information is relevant and how it can
be applied. This goes further than simply indicating
trends and adds a sixth and seventh step to the big data
approach, data — filter — context — process — analysis
— action — benefit.
MONITORING THE HEALTH OF ASSETS
There have already been some limited applications
of the value of big data through the use of predictive
analytics. These focus on better monitoring of usage
patterns and the essential tracking and analyzing of the
health of equipment and troops on the ground in real-
time. This is where the ‘action’ and ‘benefit’ step of the
big data model can provide operational and budgetary
improvements. For example Health Usage Monitoring
(HUMS) data from a fleet of scout tanks can be applied
to form an optimized fleet maintenance schedule —
with the benefits of saving time, maximizing resources
and reducing costs.
But this can go even further. In particular, the greatest
potential for big data in A&D is when predictive
analytics is used in relation to the ongoing maintenance
of equipment. The real improvement that is coming
from the sophisticated analysis of big data for A&D
is that of predicting unplanned maintenance. Why?
Because it is possible to foresee the maintenance
requirements of any asset and then, at the fleet level,
reduce the time that assets are out of action; and
preparations can be made to ensure that it has little to
no impact upon operations.
PREDICTING UNPLANNED MAINTENANCE;
THE FUTURE OF BIG DATA IN A&D — SEEING
THE WOOD FROM THE TREES
Unscheduled or unplanned maintenance is a real
problem in the A&D industry as it means that assets
have to be withdrawn from operations often at short
notice. If we are to apply this to an extreme, but not
unrealistic, scenario in an active combat environment,
this could be incredibly serious. If potentially life-
protecting equipment is withdrawn at short notice it
can degrade mission success — lives are at stake.
This is where the benefits of predicting unplanned
maintenance can really make a difference. Picking out
the relevant data patterns being fed back out of the
myriad items of information which are being produced
through big data will allow the true benefit of scheduled
maintenance to be extended into every aspect of the
support chain. More information will be available to
understand when parts need servicing or replacing and,
along with other technological advancement, potential
down-time can be drastically reduced.
BIG DATA ALREADY AT WORK —
PROVEN BENEFITS
Previous examples of predictive analytics, using
techniques such as Reliability Centered Maintenance,
when applied to a real life scenario, have reduced
combat systems maintenance in the UK for the MOD
typically by half annually with cost savings estimated to
be around 20% during the use of the solution.
EXTENDING THE CURRENT SUPPORT CHAIN
— JOINING THE DOTS
Building on this, a completely streamlined support
chain which is pre-emptive rather than reactive from
the use of big data is the big dream for the A&D
industry. Eliminating all unscheduled maintenance
may be considered unrealistic — but big data can bring
A&D as close as possible to that goal.
We have already seen that planned support is able
to significantly reduce asset down-time and costs
through careful planning. Big data is a concept and
technological possibility that now needs to prove itself.
“Theproblemtodatehasnotcomefrombigdataitself,ithascomethroughthe
interpretationofthatdata–wesimplydonotknowwhichpatternsarerelevant
andwhicharen’t,andhowtoturnthemintoarealizablebenefit.”

11. 40 | WHITE PAPER: IFS | AIRCRAFT IT MRO | OCTOBER/NOVEMBER 2015
There is an incredible amount of information that has been gathered and is waiting to
be put to use. The dots just need joining up in the correct order to understand — but
not necessarily to draw — the big picture, and to turn that into real budgetary benefits.
This needs to be done in a measured and timely way so as not to disrupt the current
support eco-system. Flexible modular software solutions make it possible for this
to happen. Collecting the data and feeding through an application allows jobs to
be correctly prioritized, unlike a lot of inflexible and complex traditional software
solutions, the architecture provides the agility for organizations to focus on the
applications that are important right now.
THE FUTURE OF BIG DATA IN A&D
The scope of millions of intelligent devices that can communicate through the Internet,
driven by emerging disruptive technologies such as the Internet of Things, opens
up new possibilities to move from our traditional reactive type of business model to
become much more proactive, where A&D can apply the data they collect to predict
and prevent faults before they happen — a particularly key consideration for A&D
organizations.
The challenge to harness and utilize big data is being seriously taken up across
the sector. For instance, the R&D facility at IFS Labs is continually working on
new developments to help organizations to manage data in a number of areas. One
of its latest research projects is IFS Pulse, a new developmental dashboard for IFS
Applications that provides real-time interaction of all the key data streams from
social media and RSS feeds to ERP data — providing a granular level of detail on
user activity at any given time. While this is developmental at this stage, IFS Labs is
adding the process and action steps which go further than simply indicating trends
from existing data. This is giving real insight into where the future lies in terms of
real-time applications for this data and unplanned maintenance — reducing costs and
revolutionizing the current A&D support chain.
BRENDAN VIGGERS
Brendan Viggers has held the role of Product & Sales Support
for the IFS Aerospace & Defense Centre of Excellence, since the
beginning of 2012, responsible for strategic product management
activities as well as development and communication of a five year
product roadmap for the A&D markets. He also has responsibility for
the Corporate Performance Management solution delivered through
one of IFS’ product partnerships. Brendan has been with IFS since 2007, with
previous roles including Product Services Manager and Senior Consultant on
the F35 ALIS Retail Supply Chain Management project and Business Application
Manager at Babcock Support Services.
IFS
IFS Applications offers flexible, module based business solutions that
manage the entire civil aviation lifecycle of contracts, projects, MRO,
assets and services. Applications include functionality for contract and
project management, risk management, budgeting and forecasting,
engineering, material management, sub-contracting, document management,
fabrication, service and maintenance management, as well as financials and
human resources. Being component-based, it is easier to implement and can be
incremental to align with the growth and scope of a business.
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12. Visit conference website: http://www.aircraft-commerce.com/conferences/Bangkok_2015/Home.asp
For further information contact Stephen Keeble – stephen@aircraft-commerce.com; +44 1403 230 888
AIRLINE & AEROSPACE MRO & FLIGHT OPERATIONS IT CONFERENCE
28th & 29th October 2015 – Amari Watergate Hotel, Bangkok, Thailand
APAC
“Airlines will be doing themselves an injustice not to attend this event”
Cathay Pacific Airways
Vendors exhibiting their software include: Lead Sponsor: