The Digital Twin:A Radical New Approach to IoT

IOT DevCon 2017Dimitri Volkmann, Digital Twin Thought Leader, GE Digital

www.linkedin.com/in/dimitrivolkmann

@dimiexter

www.pinterest.com/dimitrivolkmann/digital-twin/

Economic Power is Shifting(Credits: Geoffrey A. Moore – published April 12, 2017 on LinkedIn & Twitter)

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Records, Transactions

Communication, Collaboration

Physical Systems

DematerializationVirtual

PairingDynamicLearning

Interactive

First Wave Second Wave

Digitalizing the world

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Digital twins are dynamic digital representations that enable companies to understand, predict and optimize the performance of their machines and their business.

Digital twins are a persistent digital model of the structure, behavior and context of a physical industrial asset.

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

The Digital Twin Canvas

Digital twins are dynamic digital representations that enable companies to understand, predict and optimize the performance of their machines and their business.

Asset Data , Metadata & Events Insights (Industrial Intelligence)Structure• CAD Model & Specs• BOM• Asset Model• …

Behavior• Sensors reading• Events• Control Systems

Gold DataTraining Data

Models &Orchestration

Context• Environment• Configuration• History (Service, etc)• …

Analytics Kernels(physics)Specific Outcomes

Early warningsPredictions

Optimizations

Machine Learning(Model Training)

In Out

Dat

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Dat

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Predix Platform

AssetConnectivity

DataPersistence

Model Execution

ContinuousLearning

Machine Learning(Auto Data Modeling)

Edge to Clouddata & compute

Digital Twin APIs (Context, KPIs, Insights)

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Digital Twin: Technology Value

Context Data – The Past3D model, eBOM, Service Records, First Date of operation…

KPIs – The PresentSensors Reading, Performance, Current State…

Insights – The FutureFailure Modes, Early Warnings, Predictions…

www.formula1.com

Context

KPIs

Insights

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Asset-centric, Industrial Application Types

- Monitoring &Health- Diagnostics

- MaintenanceOptimization- ReliabilityManagement

- PerformanceOptimization- Compliance

- OperationsOptimization

- Asset Strategy

- BusinessOptimization

- New BusinessModels &

Services

PhysicalSystem

DigitalTwin

IndividualAsset level

Operations/Enterprise

level

- Simulations

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Digital Twin Development Paradigm

BUILD; MANAGE, RUN, PERSIST & LEARN; CONSUMME

1

2

3

BUILD: Asset Experts team up with data management, data scientist, analytics and machine learning specialist to BUILD Digital Twin Classes – for a specific class of Asset or System – in order to assemble data and models for identified desired outcomes. These Digital Twin Classes are published in a catalog.

RUN: Digital Twins instances for identified Assets or Systems are persisted, executed and optimized on the Platform. As more Digital Twins run on the Platform, the Learning System improves the Digital Twin Models. The Platform also offers Digital Twin management.

CONSUME: Digital Twin offers Context Data, KPIs and Insights about an Asset or System. This value is accessible through APIs and is used to build Industrial Internet Apps such as APM from GE Digital.

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Deployment: Edge to Cloud

CLOUD EDGE NETWORK

• Cheapest • Very Big Data• Very Big Compute &

Machine Learning• Compliance &

Auditability

• Lowest Latency• Lots of low relevance

data (filtering)• Resilience• Governance

• Many to many interactions

Most deployment will use a distributed model Edge/Network/Cloud depending on specific requirements, the Platform can self adjust based on learning

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Why a Digital Twin Platform?

• “Where Digital Twins live”

• Data and IP Governance

• Monetization of Data, IP and Outcomes of the Digital Twins

• Learning System

• Scale

• Management & Compliance

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

The RDBMS Analogy

RDBMS DIGITAL TWIN PLATFORM

Digitalize Information Systems & records Digitalize Physical System

Tables, Index, Clusters, Stored Procedures Digital Twin Class

Records Digital Twin Instances

SQL: DDL (Tables & Views) and Stored Procedures

Digital Twin Class (Data, Metadata, Analytics, Models, etc)

SQL: SELECT, INSERT, UPDATE, DELETE APIs Calls for Context, KPIs, Insight

RDBMS Engine: persist data, optimize queries Digital Twin engine: persist data, optimize Analytics, Learning System

Database Designer, Database Analyst Asset Experts, Digital Twin Class Designers

Database Developers Industrial Apps Developers (use APIs)

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

Getting Started Today with Digital Twins: www.predix.io

Design Principles

• Manage the Data, expose relevant Data (past, present)

• Build Models & Analytics for re-use

• Orchestrate to deliver specific outcome: KPIs, early warning, predictions

• Expose as API (de-couple from UI/UX)

GE Digital 2017, no Reproduction – IoT DevCon Conference April 2017

IOT DevCon 2017Dimitri Volkmann, Digital Twin Thought Leader, GE Digital

www.linkedin.com/in/dimitrivolkmann

@dimiexter

www.pinterest.com/dimitrivolkmann/digital-twin/

Thank You!