rolls-royce data – strictly private 5 steps to heaven – a rolls-royce perspective ibm almaden...

Rolls-Royce data – strictly private

5 Steps to Heaven – A Rolls-Royce Perspective

IBM Almaden Institute, San Jose7th May 2008

Dr Ian K Jennions

EHM Global Capability Owner

©2008 Rolls-Royce plcThe information in this document is the property of Rolls-Royce plc and may not be copied or communicated to a third party, or used for any purpose other than that for which it is supplied without the express written consent of Rolls-Royce plc.

This information is given in good faith based upon the latest information available to Rolls-Royce plc, no warranty or representation is given concerning such information, which must not be taken as establishing any contractual or other commitment binding upon Rolls-Royce plc or any of its subsidiary or associated companies.

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© 2008 Rolls-Royce plc

5 Steps to Heaven – A Rolls-Royce

Perspective

Introduction

Our Service Business

Asset Management

Business Landscape

5 Steps to Heaven

Simulation of Total Care

Value in Data

Technology Successes

Marine EHM (Equipment Health Management)

AE3007 HP Vane

QUICK

Future

Current Issues

Summary

3


Rolls-Royce’s four markets

4


Rolls-Royce Group plc - 2007

5


Video: ‘New Thinking, Joined Up Thinking'

6



Perspective

Introduction


Asset Management

Business Landscape

5 Steps to Heaven


Value in Data



AE3007 HP Vane

QUICK

Future

Current Issues

Summary

7


Changing Customer Requirements

Traditional Support Spare parts Repair & overhaul

Enhanced Support Data & forecasting

services Technical & logistics

support Customer training

Advanced Support Comprehensive package integrating

elements of basic and enhanced support Spares inclusive R&O contracts

Total Support Complete, availability- based service. Can cover

all off-aircraft, and some on-aircraft activity Configuration management & reliability

enhancements covered

Extended Support Partnered capability to cover complete weapon systems Turn-key services Non-propulsion related support solutions

Increased Scope

Cu

sto

mer

Val

ue

Rea

ctiv

e

Ali

gn

ed

Inte

gra

ted

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The EHM Transformation Staircase - Defence

Increasing Scope of Service Provision

Increasing Scope of Service Provision

Basic EHM

- Lifing – cyclic counts- Digital borescope

Advanced EHM- Lifing- Performance trending- Oil trending- Vibration trending- Improved life counting- Basic diagnostics

Total Care EHM- Data fusion –

oil/performance/vibration- Integration with LCC &

WSG tools- Advanced diagnostic- Dynamic performance

model (COMPASS)

Customer Exploits Customer Exploits Info. to Reduce Cost Info. to Reduce Cost

Extended EHM- Piece part diagnostics- Prognostic capability- Networking of systems

(BROADEN)

Future EHM

- Unknown at this time, but could include Powerplant and/or platform health monitoring

Commodity Commodity ServiceService

RR Exploits Info. to Increase RR Exploits Info. to Increase Cost Effectiveness of Product Cost Effectiveness of Product

Stage 1

Stage 2

Stage 3

Stage 4

Stage 5

Basic Support

Traditional

Enhanced Support

Forecasting

Total Support

Engine Availability

Advanced Support

Asset Management

Extended Support

Total Management

Customer Risk Customer Risk Service Provider Risk Service Provider Risk

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Total Care Simulation - Example

Product Operation aircraft, engine, airport,

operations control

Product Behaviour engine, module, part, virtual

characteristic

Asset Management parts, modules, dedicated &

lease pool spare engines, operator interaction

Manufacturing & Supply aircraft, engines, modules,

parts

Transportation & Logistics engines, modules, parts

Engine Repair, Overhaul & Test capacity, capability, resourcing, availability

Component & Module Repair

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Total Care Simulation- video

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–– –

Integrated Products and Services (IPAS)

–– –

Service Engineers/Overhaul trained and motivated to share knowledge with design. Tools, methods and processes available to support data and knowledge capture

Product designed to support the service offering –existing service knowledge base fully used, continuous improvement via optimized IPAS Processes

Designer able to search easily for knowledge via intuitive interface, ontology models and social solutions. Able to do LCC trade-offs, understands service needs

Designer Knowledge

Desktop (WP1)

LCC Modelling Toolkit (WP3)

Service Data

Product Designer

Service Engineer/ Overhaul Shop

Social Issues and Solutions (WP1)

–

Customer Customer

Customer

Optimised IPAS Processes

Key:

Service Engineers/Overhaul trained and motivated to share knowledge with design. Tools, methods and processes available to support data and knowledge capture

Product designed to support the service offering –existing service knowledge base fully used, continuous improvement via optimized IPAS Processes

Designer able to search easily for knowledge via intuitive interface, ontology models and social solutions. Able to do LCC trade-offs, understands service needs

Designer Knowledge

Desktop (WP1)

LCC Modelling Toolkit (WP3)

Service Data

Designer Knowledge Desktop

LCC Modelling Toolkit

Service Data

Product DesignerProduct Designer

Service Engineer/ Overhaul Shop

Service ProviderService Provider

Social Issues and Solutions

New (IPAS)

Existing

New (IPAS)

Existing

–

CustomerCustomer Customer

New (IPAS)New (IPAS)

Knowledge flow

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The IPAS System Architecture

KnowledgeDesktop

SDMSAP RCP Reports Other

LegacyDoc

LegacyData

Source2

NewDoc

NewData

Source4

ETC Data

Information

Knowledge

K-Search

K-Forms

Mechanisms

Features

Parts

Materials

Data Types

Ontologies

K-Forms

Web Services

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Legacy data is largely unstructured and is captured and stored in a variety of ways.

Development of ontologies for hardware description, failure mechanism etc. allow us to make sense of unstructured legacy data.

K-Search provides a means of interrogating legacy data and presenting structured search results back to the user

K-Search is a learning system that builds an understanding of document content such that after the ‘learning process’ >95% rate of correct automated document content classification can be achieved.

IPAS Results – the ability to search legacy data

Automatically extracting knowledge from legacy unstructured data

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Perspective

Introduction


Asset Management

Business Landscape

5 Steps to Heaven


Value in Data



AE3007 HP Vane

QUICK

Future

Current Issues

Summary

15


Marine Off-shore Supply and Service Vessel

Propulsion units monitored: 4 Bergen 6 cylinder C

engines. 2 Azipull thrusters. 2 Tunnel thrusters. 1 swing up thruster.

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Ethernet

Propulsion

EHM unitEngines

EHM unit

Thrusters

EHM unit

Engines

Data Coll. unit

RRM

Ship network

EHM

Central unit

RRM

Service Centre

Vessel 49 EHM Network Installation.

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AE3007 HPT Vane Distress

Leading edge burns away over time Causes: cooling blockage, oxidation Condition that typically occurs on high time engines

(primarily on-condition engines) Causes increased stress on the 1st stage blade leading to

high cycle fatigue (secondary damage) Turbine blade fracture leads to in flight shut down and a 2x

shop visit cost

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AE3007 HPT Vane Distress

Vane distress showed up as performance changes. Data fusion allows clear signature to be set

Fuel flow, turbine temp, pressure & speed 50 hour window after detection with 96% confidence of

preventing HPT blade failures Allows time to schedule removal Thresholds set to balance false positives and false negatives Relatively small number of false alerts and false negatives

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AE3007 HPT Vane Distress - Savings

The alternative of not having EHM for this issue Allow HPT-1 blade failures Pull engines in mod campaign Implement a 50 hr boroscope inspection interval

8 yr EHM Savings estimated at over $60M Based on mod campaign or inspections both ($$$$) Savings continue as engines age and experience vane

distress

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So What’s the Problem ?

With high-integrity systems such as jet engines, conventional fault detection methods have limited capability:

The most important examples (i.e. the abnormalities) are very rare Some of the fault conditions may not have been seen before Subtle pre-cursor events often exist prior to failure but these are rarely detected by employing conventional techniques.

Advances being made at RR via advanced computational and signal processing methods, specifically:

QUICK, learn a description of normality and test against it (OBS) Crack detection and propagation (Cranfield University) Knowledge Based Diagnostics (Sheffield University) DAME (Universities of York, Leeds, Sheffield and Oxford)

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Quantitative User friendly Intelligent Collection of Knowledge (QUICK)

QUICK is a system used for real time acquisition and intelligent analysis of vibration and performance data from gas turbine engines.

QUICK has been developed over a number of years between Oxford University, Oxford BioSignals and Rolls-Royce

The innovation in the product lies in:

The use of Computational Intelligence to quantify features Building models of normality Fusion of data from disparate sources for engine diagnostics. The system is exploitable in other fields (e.g. medical)

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QUICK video: Innovation Award

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Novelty Thresholds – Bayesian EVTNovelty Thresholds – Bayesian EVT

2323

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© 2008 Rolls-Royce plc 2424

Example results – 826 testsExample results – 826 tests

Method 1: Bayesian EVT Method 2: Classical EVT Method 3: Expert Heuristic

Data Set Sensitivity Specificity Sensitivity Specificity Sensitivity Specificity

A1 0.75 1.00 0.75 0.97 0.75 0.93

A2 1.00 1.00 1.00 0.90 1.00 1.00

B1 - 1.00 - 0.99 - 0.99

B2 - 1.00 - 0.85 - 0.45

B3 - 0.99 - 0.70 - 0.68

B4 - 1.00 - 0.70 - 0.65

Overall 0.78 0.99 0.78 0.83 0.78 0.73

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Perspective

Introduction


Asset Management

Business Landscape

5 Steps to Heaven


Value in Data



AE3007 HP Vane

QUICK

Future

Current Issues

Summary

26


Different perspectives – system boundaries

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EHM Intelligence Dichotomy Fleet centred view - the realisation of full value by having an accurate, real time fleet view of the

state of all assets Platform centric view - Devolving EHM intelligence to the local platform to compensate for:

– limitations in communicating with a central information hub (a lack of infrastructure and capacity)

– Requirements for assets to operate and be maintained autonomously– Concerns for data privacy and IPR

LOCAL PLATFORM

Often has to operatedeployed and autonomously,

and often has an ability toself maintain. If the platform

is mobile, datacommunications may be

limited

Data Communications infrastructure

CENTRAL HUB

Processes EHM datacentrally and issuesalerts. Maintains an

overview of the conditionof the full fleet. Is able tomitigate the operational

consequences offailure

LOCAL PLATFORM


and often has an ability toself maintain. If the platform

is mobile, datacommunications may be

limited

LOCAL PLATFORM


and often has an ability toself maintain ‘on mission’. Ifthe platform is mobile, datacommunications channelsmay change and be limited

Communicationsbandwidth may belimited and may be

expensive

Real time monitoring offers advantages ofbetter resolution, earlier detection and a

wider scope of failure mode detection - atthe price of having to process much

higher data volumes

Some organizationsdo not want to export

their data beyondtheir firewalls

THE RESULT IS PRESSURE TO PUSH EHM INTELLIGENCE TOWARD THE PLATFORM

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Vision: HUMS Information Fused with Operations for Optimised Fleet Management

SAP

CoreControlCoreAlert

Service Data Manager Aero Exec Integrator

Gold (T45 Programme)

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Vision: The Operations Room of the Future?

Oil uplift and utilizationdata transferred from

Squadron and pilot reports

EHUMS data download from A/C using data retrieval unit (DRU)

routed via Ground Support System (GSS) to Operations Centre

Customers alerted by pager, e-mail or cell phone

Customers can view status on DefenceManager

Operations Room - processes information

Service team monitors output and liases with customer

Repair and Overhaul

Agent-based aftermarket modelling and decision

support

All Operations linked through global GRID system

AI fault recognition and diagnosis

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5 Steps to Heaven - Summary

In the OEM to Service business transformation data is key

Operating on the data to create information and knowledge has been demonstrated, including value, in a number of areas.

With risk shift from Customer to OEM in a Service model EHM is risk mitigation, informing the Aftermarket business and helping to minimise unplanned events

Basic EHM has been yielding good results for a number of years, the next steps are much more complicated

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© 2008 Rolls-Royce plc http://www.cranfield.ac.uk/cua

Vision A world-class research and demonstration Centre of Excellence, seeking to establish industry standards and yielding competitive advantages in Integrated Vehicle Health Management (IVHM) for its industry members.

Strategic Aims • Attract Investment – supplement launch funding by attracting additional investment from new core partners/members and research funding bodies• World Recognition – working with industry and academic leaders• Technology Transfer – implementation of concepts and technologies within the industry and develop the associated skills base• Self Sustaining – after 5 years• Delivery of Competitive Advantage – to the key stakeholders

Cranfield Integrated Vehicle Health Management Centre of Excellence

Generic Architecture

CoE Concept Funding/ Governance

rolls-royce data – strictly private 5 steps to heaven – a rolls-royce perspective ibm almaden...

Documents

rollsroyce data

rollsroyce plc video

property of rollsroyce

rollsroyce plc rollsroyces

thinking slide

future ehm unknown

cost extended ehm piece

availability based service