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Confidential. Not to be copied, distributed, or reproduced without prior approval. © 2017 Baker Hughes, a GE company, LLC - All rights reserved.

APM: Driving value with the Digital Twin

September 18-20, 2017

Mark Wise Senior Director, GED Applications Strategy

© 2017 Baker Hughes, a GE company, LLC - All rights reserved.

Confidential. Not to be copied, reproduced, or distributed

without prior approval.

Safe Harbor

CAUTION CONCERNING FORWARD-LOOKING STATEMENTS:

This document contains "forward-looking statements" – that is,

statements related to future events that by their nature address

matters that are, to different degrees, uncertain. For details on

the uncertainties that may cause our actual future results to be

materially different than those expressed in our forward-looking

statements, see

http://www.ge.com/investor-relations/disclaimer-caution-

concerning-forwardlooking-statements as well as our annual

reports on Form 10-K and quarterly reports on Form 10-Q. We do

not undertake to update our forward-looking statements. This

document also includes certain forward-looking projected

financial information that is based on current estimates and

forecasts. Actual results could differ materially. to total risk-

weighted assets.]

NON-GAAP FINANCIAL MEASURES:

In this document, we sometimes use information derived from consolidated financial data but not presented in our financial

statements prepared in accordance with U.S. generally accepted accounting principles (GAAP). Certain of these data are considered

“non-GAAP financial measures” under the U.S. Securities and Exchange Commission rules. These non-GAAP financial measures

supplement our GAAP disclosures and should not be considered an alternative to the GAAP measure. The reasons we use these non-

GAAP financial measures and the reconciliations to their most directly comparable GAAP financial measures are posted to the

investor relations section of our website at www.ge.com. [We use non-GAAP financial measures including the following:

• Operating earnings and EPS, which is earnings from continuing operations excluding non-service-related pension costs of our

principal pension plans.

• GE Industrial operating & Verticals earnings and EPS, which is operating earnings of our industrial businesses and the GE Capital

businesses that we expect to retain.

• GE Industrial & Verticals revenues, which is revenue of our industrial businesses and the GE Capital businesses that we

expect to retain.

• Industrial segment organic revenue, which is the sum of revenue from all of our industrial segments less the effects of

acquisitions/dispositions and currency exchange.

• Industrial segment organic operating profit, which is the sum of segment profit from all of our industrial segments less the effects

of acquisitions/dispositions and currency exchange.

• Industrial cash flows from operating activities (Industrial CFOA), which is GE’s cash flow from operating activities excluding

dividends received from GE Capital.

• Capital ending net investment (ENI), excluding liquidity, which is a measure we use to measure the size of our Capital segment.

• GE Capital Tier 1 Common ratio estimate is a ratio of equity

Confidential. Not to be copied, distributed, or reproduced without prior approval.

Introduction to GE Digital


Advancing the horizontal and vertical

September 28, 2017 4

™

$6 B USD


GED APM growth initiatives



APM and currentmarket conditions


APM market overview | industry landscape


Strategicinnovation

Top 7 industries cover 65% of total market of $7.8 B USD in 2017

Total Addressable Market (TAM)

Drivers and Industry Challenges

• Healthy top line, but with pressures on bottom line — need profitability enabler

• Assets are aging

• Regulations are increasing and tightening

• Operational uncertainty

• Process variability

Oil &Gas Power Gen Chemical Machinery Mining Aero Pulp & Paper

$1,890 $1,440 $ 5 7 0 $ 2 8 0 $ 3 5 2 $293 $ 2 6 7

1,360

1,053

783

570

529

387 352293 280 267 239 233 231 216 212

189 169117 104 104

65 38

2017

2018

2019

Numbersin chart–

2017 TAM

$MM


Oil and gas industry challenges


Strategicinnovation

60%Cite maintenance and

reliability as a top priority

70%Decline in oil price

since June 2014

8

50%Of workforce to retire in the

next 5 to 10 years. Knowledge & experience

not being transferred

49%Estimated increase in EH&S spending among global E&P

companies

~$10,000/hrfor a 2000 hp natural gas

compression stationincrease in inventory, labor costs, delayed

delivery, and reduced profitability

5-10%3-5%of lost production in

oil and gas

10xthe cost for unplanned

events vs. planned maintenance in process

industries

Potential Value to the Industry =

~$1 trillion USDFor Digital

Transformation


High data volume and velocity — and will increase


Upstream

• Drilling data 0.3 GB / well / day

• Wireline data 5 GB / well / day

• Fiber optic data 0.1 GB / well / day

• ESP monitoring 0.4 GB / well / day

• Seismic data 100 GB / survey

Hundreds to tens of thousands of assets per site

Industrial data requires a fundamentally different approach than transactional data

Midstream

• Process data 4 GB / plant / day

• Atmospheric data 0.1 GB / plant / day

• Pipeline inspection 1.5 TB / 600 KM

Downstream

• Process data 6 GB / plant / day

• Operational data 8 GB / plant / year

• Vibration data 7.5 GB / year / customer

Inspections

• Ultrasound: Tubes 1.2 TB / 8 hours

• Corrosion monitor 1 GB / site / year

ERP systems Predix

Data from industrial assets will dwarf data in ERP system

• ~10-100x more volume

• ~100-1000x more velocity

ERP Systems

• Transactional data

• Logistics reports

• Maintenance logs

• FSE reports

• Inventory reports


GE Digital APM: Single Enterprise Application

Fragmented, discrete solutions lead to data storage and workflow silos

GE defragments point solutions


10


Markets built on a model


ERP – built on financial model

$41.69 B USD market by 20201 $123 B USD market by 20213$48.5 B USD market by 20202

CRM – built on the customer model lloT – built on the asset model

By 2025 IIoT expected to deliver

$8.6 trillion USDin value on an annual basis


September 28, 2017 12September 28, 2017 12


This Industrial Expertise Uniquely Positions GE to Deliver on the IIoT Promise

Design179,396 patentsgranted

Build450+

factories in 45 countries

Connect$1 trillion USD +

In assets continuously

monitored

Operate1/3 world’s electricity is

generated withGE technology

ServiceMonitor and Maintain

70% of theworld’s LNG isunder a BHGE

service contract


13

BHGE Digital Product Portfolio Architecture

Cost Output Response TimeAzure AWS GE Private Cloud

Digital Twin Framework

Machine andEquipment Health

Compliance and Integrity Management

Asset Strategy Optimization

Reliability Management

Asset Performance Management(APM)

APM Shared ComponentsCase Mgmt, Knowledge Mgmt, Alarm, Asset Mgmt, Condition

Monitoring, SmartSignal, Visualization, and More

Predictive Corrosion

Management (PCM)

BHGE Digital Other

Products* (LNG, Refinery, etc)

IntelliStream™

SaaS Applications

SaaS Applications

BHGE Oil and Gas DigitalProducts

OT Sys

PLM Sys

ERP Sys

IaaS

PaaS

* New products under development by BHGE Digital


GE Digital APM solution map


• Achieve less unplanned downtime

by predicting equipment issues

before they occur.

• Ensure asset integrity and

compliance by monitoring

changing risk conditions.

• Optimize across availability,

reliability, risk, and costs

through intelligent asset

strategies.

• Predictive diagnostics

• Case and collaboration management

• Knowledge management

• Root cause analysis

• Reliability analysis

• Hazard analysis

• Safety lifecycle management

• Risk based inspection

• Inspection management

• Thickness monitoring

• Management of change

• Reliability centered maintenance

• Failure mode and effects analysis

• Strategy management

• Strategy library

• Lifecycle cost analysis

• Financial and risk simulation

Anytime, anywhere, unified view of your assets’ current state and health.Machine & Equipment Health

Reliability ManagementCompliance & Integrity

Management Asset Strategy Optimization

• Connectivity • Data management• EAM integration

• Condition monitoring • Data analysis and visualization• Criticality analysis

• Event management • Recommendation management• Reliability benchmarking


GE APM – continuous improvement framework


Strategy

RiskOperations and

maintenance

Analyticsand action

Change strategy

Drive work /repair

ReliabilityManagement

Compliance and Integrity Management

Asset strategy Optimization

Machine and Equipment Health

Re-evaluate risk

Criticality failure modes

Damage mechanisms Optimize plan

Connect / collect• Sensor data / alerts /

events• Inspection / work

history events

1. Identify criticality of assets

2. Identify asset failure modes / degradation mechanisms

3. Build, manage and optimize strategies

4. Integrate / execute strategies and collectperformance data

5. Monitor asset health through condition and predictive methods

6. Drive recommendations and strategy / risk re-evaluations

7. Ensure APM governance and measure program effectiveness


Business benefits



2-6%

Increasedavailability

5-10%

Inventory cost

reduction

10-40%

Reduction in reactive

maintenance

3-40%

HSEincident

reduction

5-25%

Gain inemployee

productivity

5-25%

Reduction in IT totalcost of

ownership

GE is the only APM solution providing end-to-end value


Recent study on APM expectations….


17

• Operating companies can expect to reap huge benefits from APM

• Implementing APM requires significant time and effort to implement new work processes, enabling technology, and training employees

Impact of unplanned downtime on productionSource: ARC Survey of Senior Executives and Engineering, Operations, and Maintenance Managers in Oil and Gas)

Expected benefits of APM

Improved safety

Percent of respondents


Digital Twinspowered by APM


Digital Twin



defines a digital twin as:

“A dynamic software model of a physical thing or system that relies on sensor data to understand its state, respond to changes, improve operations and add value.”

“Digital twins are becoming a business imperative, covering the entire lifecycle of an asset … and forming the foundation for connected products and services. Companies that fail to respond will be left behind.”

© 2017 General Electric Company - All rights reserved

Digital Twin’s at GE

Drive Business Outcomes

Per Asset

Continuously Learns

Scalable

Adaptable

1

2

3

4

5

Digital Twin are digital representations of industrial assets and processes combining data and knowledge of assets and processes with intelligence in the form of analytics, models, rules, or additional code to drive a specific outcome.

Physical Asset Digital TwinA Learning Digital Model



Digital Twin Blueprints


• Applied by asset class

• Leveraged within APM for specific, individual assets

• Contain pre-defined:

• Failure modes – Known set of failure modes from most comprehensive library on the market of how equipment fails

• Strategies – Optimized set of recommendations by asset class

• Analytics – Predictive and diagnostic analytics catch and identify failure modes early

• Health indicators – Distinct measures define and manage asset conditions

• Metrics – Asset-level KPIs to measure performance

• Life cycle costing – Tools to model historical and operational datasets to determine true asset lifecycle costs and performance expectations

DIGITAL TWIN

BLUEPRINT

ASSET STRATEGY

FAILURE MODES

LIFE CYCLECOSTS

METRICSKPIS

HEALTHINDICATORS

ANALYTICS


If APM is the engine, then digitaltwins are the fuel


Strategy

RiskOperations and

maintenance

Analyticsand action

Change strategy

Drive work /repair

Reliabilitymanagement

Compliance and integrity management

Asset strategy optimization

Machine and equipment health

DIGITAL TWIN

BLUEPRINT

HEALTHINDICATORS

ANALYTICS

ASSET STRATEGY

FAILURE MODES

LIFE CYCLECOSTS

METRICSKPIS

ANALYTICS

ASSET STRATEGY

FAILURE MODES

LIFE CYCLECOSTS

METRICSKPIS

HEALTHINDICATORS


ASSET STRATEGY

FAILURE MODES

LIFE CYCLECOSTS

METRICSKPIS

HEALTHINDICATORS

ANALYTICS






DIGITAL DRILL RIG


KPIs to Data: Digital Twin Blueprints

APM KPI Industry Equipment Type Failure ModesAnomaly

Detection Analytics Health Indicators

Reliability

Availability

Maintenance Costs

Driven by

Pump

Motor

Heat Exchanger

…

Bearing Wear

• Fatigue….• …..

…

Policies

SmartSignal

Physics Based, Engineering & Machine Learning

Temperature, Pressure, Vibration..

Compliance, Operational Risk..

Other….

Analysis of Failure Modes by Equipment Type Analytics Catalog Data Catalog


Oil & Gas

Renewables

Power

Transportation

Marine

Mechanical Seal

• Leaks• …..

Risk


Analytics Orchestration: Customer Use Case

Layering multiple algorithms helps create better outcomes

Condenser issue detected3 hours prior to event

Legacy Analytics: Good

111/1711/1611/1511/1411/1311/1211/1111/1011/911/811/7

2

Improved Analytics: Better

Condenser issue detectedone day earlier

3

APM Analytics:

Next Generation

Condenser issue detected10 days earlier

Condenser Issue Detected 10 days earlier

+

+




Value of the Digital Twin

Move up the PF curve… .. and stay there

Time

Ma

ch

ine

/pro

ce

ss e

ffe

cti

ve

ne

ss

Proactive maintenance PredictiveOptimize maintenance Break/fix

Functional failure Equipment offline (Trip)Full functionality

Machines and processes are running normally

Early signs of failure exist in data Alarms / Alerts

Equipment or

processes are not producing

Predictive


Digital Twin Solutions Today


WEEKS MONTHS YEARS

Time to Value

Industry Count of SSAnalytics

Chemicals 10

Defense 5

Oil & Gas 48

Power 114

Transportation 21

Mining 28

TOTALS 234

• 60 analytics for asset coverage

• 30 Digital Twin physics and engineering models

• 100 Digital Twin machine learning methods

• 111 granted patents deliver differential value

• Asset Strategy Library ~ 700 Equip Types

• 50,000 Damage Mechanisms / Failure Modes

• 321 Inspection Strategies

• Standard inspection checklists

Growing Analytics Catalogue

Strategy Libraries


Fixed Equipment Example



Risk Assessment and Degradation Mechanisms



Asset Strategy



Analytics



Health Indicators



KPIs Metrics – Risk (without plan)


KPIs Metrics – Risk (with plan)

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