Presentation to the Aircraft Commerce Airline & Aerospace MRO & Flight Ops IT conference - on - Digital Twins, Digital Analytics & Digital Thread

1. Aircraft Commerce
Airline & Aerospace MRO & Flight Ops IT Conference
Miami, FL, USA
13 March, 2018
Digital Aviation: Innovation &
Disruption in MRO
Michael Wm. Denis
Principal, Aviation & Aerospace

2. 2© Capgemini 2018. All rights reserved |
Education
Michael Wm. Denis
Principal, Aviation & Aerospace
Capgemini America
3475 Piedmont Rd NE
Atlanta, GA 30305
+1 (678) 524-8289
michael.denis@capgemini.com
MS Decision Science, Robinson College, Georgia State University
BS Nuclear Engineering, Georgia Institute of Technology
Executive Summary
Michael Wm. Denis brings twenty-nine years of
experience in industrial services industries with
significant P&L responsibility in consulting, M&A
strategy, software development &
implementation and performance based
outsourcing.
Coined the term Service Lifecycle Management
(SLM) as a business and technological
capability in 2004, following years of field
analysis, R&D, and the development of eleven
patents. Deep field experience in Autonomics
and Sense & Respond Logistics, military terms
for industrial Internet of Things (IoT).
Focused on delivering performance and
subscription based XaaS solutions and
servitized business models to organizations
seeking to optimize profits of complex asset in
capital intensive, cash flow sensitive industries.
Author and columnist on business and
technology for Aviation Week, Aircraft
Commerce, and ATE&M magazines.
Exemplary Engagements
▪ Core leadership team member that led the
company to 13%, 33% and 37% CAGR over
a three year period at Flatirons Solutions
▪ Led the Product Development of Flatirons
SaaS based Mobility Content and
Compliance Management (MCCM) solution
from business case development, solution
development, solution design, pricing,
marketing and first sale and implementation
at American Airlines
▪ Developed the aviation industry standard
enterprise business and solutions
architecture for the integration of Product
Lifecycle Management (PLM), Service
Lifecycle Management (SLM) and Content
Lifecycle Management (CLM / ECM)
▪ US Airline Merger: Advised the senior
executive team during the third largest
merger of two airlines in the past twenty
years, specifically analyzing the process and
technology integration plans for their single
operating certificate and developing risk
scenarios and mitigation plans for the
technical operations division. Subsequently
conducted and prepared a board directed
post-merger IT assessment report.
▪ US Air Line Technical Operations: Multi-year
team member for the client’s “Next
Generation MRO” process reengineering and
technology architecture initiative.
Implemented multiple solutions
Skills & Qualifications
▪ Gas Turbines Engineer, US Navy
▪ Service Lifecycle Management (SLM)
▪ Product Lifecycle Management (PLM)
▪ Enterprise Content Management (ECM)
▪ Cloud / Microservices Architecture

3. 3© Capgemini 2018. All rights reserved |
Innovations in Aviation

4. 4© Capgemini 2018. All rights reserved |
Digital Twins are digital replicas of a particular asset’s
logical (as-designed) and physical (serialized as-
operated) configuration and associated parametric
data. The logical digital twin contains as-allowed rules,
baseline configurations, parametric data and
engineering limits of how an asset is designed to
function; while the physical digital twin contains the as-
maintained configuration and consumes sensor data,
operating data, utilization data, maintenance data,
environment data and effectivity changes in these
parameters over an assets lifecycle – becoming the
repository of an asset’s history and providing a single
source of truth to technicians, lessors and regulators.
Digital Twins are
always
PLURAL

5. 5© Capgemini 2018. All rights reserved |
Digital Twins by the numbers:
67.8% 71.7% $15.6B
Number of airlines
that do not
integrate their
condition or health
monitoring systems
with their core MRO
configuration mgt
systems.
Number of aviation
decision makers
who said they were
not familiar with
the industry
standards
underpinning
Digital Twins.
Value to the
aviation &
aerospace industry
ecosystems of
autonomic
capabilities and
asset performance
optimization.
Source: Capgemini 2017Aviation MRO survey and Capgemini Smart Factory survey

6. 6© Capgemini 2018. All rights reserved |
Multi-Dimensional Configuration Management

7. 7© Capgemini 2018. All rights reserved |
Structural CM
S/N’s, lot
#’s, position,
etc…
Functional CM Controls & Limits
0, 1, 2 way interchangeability rules
HW/SW interchangeability rules
Positional interchangeability rules
Operational interchangeability
rules
(c)onceived
(e)ngineered
(m)anufactured
(t)ype / model series
(u)nit / physical instance
xBoM = Bill of Material
xBoA = Bill of Assembly
xBoS = Bill of Sustainment
xBoO = Bill of Operations
PLM Virtual World (As Designed / As Planned) to SLM Physical World (As Maintained / As Operated)
As-
Conceived
cBoM
As-
Designed
eBoM
As-Planned
mBoM
As-Built
mBoA
As-
Sustained
tBoS
As-
Maintained
uBoS
As-
Operated
uBoOC o m p a r e

8. 8© Capgemini 2018. All rights reserved |
PLM Virtual World (As Designed / As Planned) to SLM Physical World (As Maintained / As Operated)
Structural CM
S/N’s, lot #’s,
position, etc…
Functional CM Controls & Limits
0, 1, 2 way interchangeability
rules
HW/SW interchangeability rules
Positional interchangeability rules
Operational interchangeability
rules
mBoA
As-
Sustained
tBoS
As-Maintained
uBoS
As-
Operated
uBoO

9. 9© Capgemini 2018. All rights reserved |
PLM Virtual World (As Designed / As Planned) to SLM Physical World (As Maintained / As Operated)
L = Logical; F = Functional and S = Structural
P = Physical; F = Functional and S = Structural
FP
SL
FL SP
Design/PlanDesign/Plan
changes inchanges in
via Effectivityvia Effectivity
CutCut--In ofIn of
ScheduledScheduled
& accounted& accounted
for infor in
in response toin response to
analysis ofanalysis of
FP
SL
FL SPSP
Design/PlanDesign/Plan
changes inchanges in
via Effectivityvia Effectivity
CutCut--In ofIn of
ScheduledScheduled
& accounted& accounted
for infor in
in response toin response to
analysis ofanalysis of
Functional Configuration Management (CMF)
is the tracking, analysis and management
of the functional design and operating
performance parameters of an asset,
assembly or component. There is a Logical
“as-designed” (FL) and Physical “as-
operated” (FP) version.
Structural Configuration Management (CMS)
is the tracking, analysis and management
of the structural piece of an assets Bill of
Material (BOM, EBOM, MBOM). There is a
Logical “as-allowed” (SL) structure and
Physical “as-maintained” (SP) version.
Effectivity (E) is the dimension that tracks and
schedules changes in one or more of the
previous two dimensions CMF or CMS in
accordance with a specific derivative.
Change derivatives can include: (EO/EAs,
Airworthiness Directives (AD), Service
Bulletins (SB), calendar time, operating
time, cycles, environment or events (e.g.,
lightening/EM radiation, bird strike, hard
landing …).
PLMPLM
SLMSLM

10. 10© Capgemini 2018. All rights reserved |
PLM Virtual World (As Designed / As Planned) to SLM Physical World (As Maintained / As Operated)
Digital Twins Operations
C o m p a r e
OD
Operational Data
Logical CM
Physical CM
Structural CM
Functional CM
Maintenance data
Sensor data
Environment data
Events data
…
ED
Engineering
Data
As-Designed
eBoM
As-
Maintained
uBoM
As-Operated
uBoO

11. 11© Capgemini 2018. All rights reserved |
Digital Analytics
make connected
things
SMART
Digital Analytics are various methods,
algorithms and tools that use digital twin data
gathered over the digital thread for component
failure and degradation prediction, predictive
maintenance, case-based reasoning diagnostics,
task and repair prescription, component and
asset prognostics, component pool health
scoring, aircraft and fleet health, fleet program
enhancements, autonomic logistics and both
operational and financial asset performance
optimization. Digital analytics include time series
analysis, Bayesian analysis, machine learning,
deep learning and autonomic decision support.

12. 12© Capgemini 2018. All rights reserved |
Digital Analytics by the numbers:
73.4% 4.8% $18.5B
Number of airlines
& MRO executives
who Strongly Agree
or Agree that data
volume & velocity
exceeds their
ability to drive
business value.
Number of airlines
& MROs using some
sort of artificial
intelligence or
machine learning
predictive
maintenance
capability.
Value to the
aviation &
aerospace industry
ecosystems of
autonomic
capabilities and
asset performance
optimization.
Source: Capgemini 2017Aviation MRO survey and Capgemini Smart Factory survey

13. 13© Capgemini 2018. All rights reserved |
Digital Transformation Capability Maturity Roadmap
TS: Time Series; BA: Bayesian Analysis; AI: Artificial Intelligence; ML: Machine Learning; RCM: Reliability Centered Maintenance; CBM: Condition
Based Maintenance; CBR: Case Based Reasoning; CF: Collaborative Forecasting; CP: Collaborative Planning; CR: Collaborative Replenishment
Prognostic Asset
Health Management
Service Resource
Execution (CR)
IncreasingFinancialValue($$$)
Increasing Operational Value (Actionable Time / Reliability / Operational Risk Reduction)
Service Resource
Forecasting (CF)
AI/ML Condition & Task
Prediction
Digital Thread &
Remote Condition
Monitoring
Predictive Maintenance Capabilities
Advanced Supply Chain Capabilities
CBR Diagnostics &
Task Prescription
Service Resource
Planning (CP)
Condition monitoring
(remote or on board)
is the capability to
capture structural
and functional data
(parametric data,
fault codes) and
deliver it to central
processing nodes
Predictive
Maintenance uses
algorithms (TS, BA,
AI, …) on parametric
data CMFP∂∆ to
forecast degradation
or failure and
criticality (FMECA) of
components in RCM
or CBM programs
Case Based
Reasoning diagnosis
is an AI method that
learns “causality” of
failure modes and
degradation CMFP∂∆
given a specific CMSP
to determine the
prescription options
for various
operational outcomes
(prognoses)
Prognosis is the
prediction of likely
outcomes given a
diagnosis and
prescription. The
Health of an asset is
the delta of its
physical functional
condition CMFP∂∆ to
its logical or as-
designed conditions
CMFL∂∆. Aircraft level
prognostic health is a
function of installed
components ΣCMSP
Autonomic Asset
Performance
Optimization
Autonomic Logistics
Autonomic
operations is the
self-learning,
autonomous and
automatic decision
support & execution
capability from the
point of operations
to the entire service
support ecosystem,
simultaneously
optimizing operation
of an asset or assets
as well as its / their
revenue, profit, cost
or economic
performance and
various trade offs

14. 14© Capgemini 2018. All rights reserved |
Continuous Airworthiness Engineering & Program Management
Maintenance, Repair & Overhaul – Planning, Scheduling & Execution
Logical HW/SW
Configuration Management
Physical HW/SW
Configuration Management
Maintenance Program
Management
EO / AD / SB Planning and
Scheduling
Time, Cycles and Conditions
Monitoring
Technical Manuals & Policies
Content Management
Legal & Regulatory Forms &
Records Management
Task Cards, SB, AD & EO
Content Management
Station Capability Planning,
Staffing & Tooling
Maintenance Operations
Control
Line / Ramp Maintenance
Execution
Hangar Visit Production
Planning & Control
Shop Visit Production
Planning & Routing Control
Shop, GSE & Tooling
Maintenance, Calibration &
Control
Hangar Maintenance
Execution
Maintenance Engineering &
Technical Support
Shop Long Range
Scheduling & Routing Mgt
Human Capital Training &
Certification
Long Range Visit Planning,
Scheduling & Slotting
Finite Human Capital
Capacity Scheduling
Autonomic Services
Autonomic Logistics
Fleet / Asset Performance
Management
Component, Program &
Dispatch Reliability Analysis
Regulatory Compliance
Management & Reporting
Human Factors Reliability
& Talent Innovation
Contract, SLA & Warranty
Management
Aircraft & Component
Reliability Analysis
Performance Based Contract
Management
Quality Management System
(QMS)
Safety Management System
(SMS)
Event, Incident & Case
Management
Predictive Analytics (Failures
& Causal Weights)
Sensors & Faults Condition
Monitoring
Prognostics, Health &
Performance Management
Case Based Reasoning
Diagnosis & Prescription
Material & Repair
Provisioning
Multi-Echelon Service Parts
Optimization
Collaborative SC Execution
VMI, Pooling & Repairs
Material Warehousing,
Distribution & Transportation
Material & Repair Finance &
Accounting
Material & Repair Planning &
Scheduling
Aerospace / Aviation SLM Reference Architecture

15. 15© Capgemini 2018. All rights reserved |
IoT analytics making the Aircraft Value Chain smart
Source: Frost & Sullivan; Industry Reports; Secondary Sources; IBC Analysis
Design &
Engineering
Manufacturing Supply Chain MRO & Flt Ops
Low Penetration
Nascent stage
High Penetration
Adoption stage
High Penetration
Adoption stage
High Penetration
Nascent stage
Penetration and Adoption Analysis of IIoT Across Aircraft Value Chain
Key IIoT Objective
To provide the basic foundation towards
building a flawless aircraft.
IIoT Benefits
▪ Minimise weight
▪ Minimise volume
▪ Maxiimise performance
▪ Maximise life
▪ Minimise lifecycle cost
▪ Strategic reuse
Key IIoT Objective
To efficiently coordinate, direct, and
oversee the production of aircraft on the
factory floor.
IIoT Benefits
▪ Planning & optimisation
▪ Quality monitoring
▪ Asset optimisation
Key IIoT Objective
To create value by forming
a competitive infrastructure using
logistics working on demand by
measuring performance.
IIoT Benefits
▪ Supply chain
▪ Optimisation, efficiency
▪ Visibility
Key IIoT Objective
To offer on-time inspection, repair,
alteration, and the supply of aircraft
spare parts.
IIoT Benefits
▪ Aircraft health monitoring
▪ Last mile connectivity
IoT can help aircraft manufacturers meet their service lifecycle warranty and service level agreement objectives across
different stages of the manufacturing to operations value chain.

16. 16© Capgemini 2018. All rights reserved |
The Digital Thread represents the digitization of
product lifecycle and service lifecycle data and the
connections between systems and organizations.
Originating from design inception through prototyping,
manufacturing, operation, in-service maintenance,
repair and overhaul, as well as training and content
support documentation. The key capabilities of the
digital thread are simultaneously maintaining data and
content interoperability for both human and machine
consumption and connectivity across the multitude of
use cases and ecosystem organizations.
Digital Twins &
Digital Analytics
require a
DIGITAL THREAD

17. 17© Capgemini 2018. All rights reserved |
Digital Thread by the numbers:
80.3% 46.5% $11.2B
Number of C-level
aviation executives
and vice presidents
that agree plugging
gaps in the digital
thread is essential
to driving business
value.
Number of airlines
& MROs that have
allocated capital
and resources to
closing gaps in the
digital thread.
Value to the
aviation &
aerospace industry
ecosystems to
closing gaps in the
digital thread.
Source: Capgemini 2017Aviation MRO survey and Capgemini Smart Factory survey

18. 18© Capgemini 2018. All rights reserved |
The Digital Thread
PLM Virtual: As Designed to As Manufactured SLM Physical: As Operated & As Maintained DCX
Autonomic Logistics
Procurement&
Distribution
Content Lifecycle Management (CLM)
Autonomic Services
Asset Performance Monitoring and Service / Product Feedback
SenseRedesign
Data Schema Definitions, Interoperability & Technical Architecture
Provisioning
mBOM & MES Manufacturing Instructions sBOM & Technical Manuals, Tasks, Forms & Records
Regulatory Forms & Certifications
ProductDesign
&Engineering
Skills, Certifications, Learning (LMS) & Human Capital Management (HCM)
Contract, SLA & Warranty
Mgt
Condition Monitoring
Diagnosis & Prescription
Prediction – Failure &
Causal Weights
Reliability, Quality QMS &
Safety SMS
Event, Incident & Case Mgt
Service Lifecycle FMECA,
MTA, LORA, Engineering,
Reliability & MRO Program
Development
IoTMonitorRespond
Manufacturing
Operations
ServiceConsumption&PassengerExperienceManagement
Device/Asset/
EcosystemService
Operations&Delivery
MRO OPS
S6000T
S1000D / iSpec2200
S4000P
S2000M / SPEC2000
S5000F
S2400/2500
S9000D
PDM
3DMBD
MOM/MES
APS/FCS
PLM
Contracts
MRP
Service Lifecycle Logistics
Support Analysis (LSA) &
Integrated Logistics Support
(ILS)
S3000L
Regulatory Reporting & Mgt
Prognosis, Health &
Performance Mgt
S8000O
S7000E
CAE
IATA & S2300
CAD
The Aviation Digital Thread logical architecture

19. 19© Capgemini 2018. All rights reserved |
eLogbook / EFB
S1000D
Collaboration
Network
Sneaker Net
▪ Sensor Data
▪ Fault Codes
▪ Operations Data
– Flight
– Crew
– Airport
– MRO
– PO / RO
▪ Environment
Data
▪ CMC / ACMS
▪ Aircraft Content
– Manuals
– IPC
– Task Cards
– Records
ACARS VHF
ACARS over IP
Ground Link
Service Bus
Digital Threads
Ecosystem
Data Hub PaaS
Data Virtualization & Distribution
Data Wrangling & Transformation
XML / JSON Conversion
Decision Optimization
AI / ML / DL Analytics Engine
Sources & Data Types Transport Paths & Vendors Digital Twins & Predictive Analytics
The Aviation Digital Thread physical ecosystem

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Copyright © 2018 Capgemini. All rights reserved.