Internal IoT Projects - Insights & Lessons Learned Projects - Insights & Lessons Learned...

Torsten Wolf, SAP EMEA GSS Head IoT

IoT Projects -

Insights & Lessons Learned

Internal

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Agenda

What is new?

The “handshake”

From the field …

Project example

Key questions to ask!

It´s a transformation

How to start?

We support you

What is new?

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12 Months Ago …

Logistics – Ship onboarding /

port water level monitoring

Chemical - Failure

Pattern Detection

Logistics - Cold

Chain Monitoring

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IoT Engagements Examples …

Logistics – Ship onboarding /

port water level monitoring

Chemical - Failure

Pattern Detection

Logistics - Cold

Chain Monitoring

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Op

timiz

e &

Act

Business

Systems

Sen

se &

Mo

nit

or

Intelligent

Assets

Analyze & Predict

Close the loop from things-to-outcome

“The Handshake”

IoT Platform

Data Storage and Provisioning

Device Mgt &

Data Integration

Business Process

Integration

IoT Platform Capabilities

IoT Applications & Analytics

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SAP ERP

SAP Syclo

SAP CRM/C4C

SAP MRS

Create Service

Order

Schedule

Service Order

CVFault Pattern

Recognition

Asset Health

Prediction

IT / OT

Connectivity

Condition Monitoring

Service Call

Intell.Assets

IoT Applicat.

IoT

Applications &

Analytics

Core Business

Processes

Execute Service

Close the loop from things-to-outcome

& “back”

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The human side is key for success

Create an open

innovation

culture … with

reiterations /

failure as part

of the

transformation

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An out of the box approach and solid change management are key for success

Unusual team

collaboration

scenarios –

Be aware of

the potential

challenges

Business

IT OT

Project example

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Example: Dynamic Maintenance Management

Transform the Maintenance Business at a Rail Operator

The Challenge

2,000 locomotives, 6M sensors

Hundreds of TBs of data per year

The Solution

SAP Predictive Maintenance

The Vision

Perform ALL the required

interventions at the RIGHT TIME,

No unplanned downtime.

Substantial reduction of costs.

CONNECTED

TRAINS

EXTERNAL

DATA SOURCES

TRANSACTIONAL

SYSTEMS

ENGINEERING

RULES

PREDICTIONS

PLANNING

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High Level Architecture

Principles

Separate Systems for Production and Engineering

Production is used to plan and predict

Engineering is used to develop prediction models and rules for planning

Defined prediction model and rules need to be deployed into production system

Only hot data in Production system

Warm data in Engineering system based on extended storage

Performance optimized even with large volumes

Endless scalability

Engineering Production

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Example: From Battery Data to Battery Health and Action

maintenance cost reduction for batteries

Battery

=

Fleet Level Information

Machine Level Information

Compare and analyze real time

battery performance to ideal state

Real Time Data Ideal State

Collect Real Time

Telemetry Data from Batteries

PdMS Application shows insights about health

score of machines and business information

Insights

ERP + MRS

Maintenance

Schedules

& Financial

Information

Action

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Conceptual Impact on Maintenance Activities

• Absolute reduction of maintenance activities and costs

• Shift from static planned and corrective maintenance, to dynamically planned

Dynamic Planned Maintenance

Static Planned Maintenance

Corrective Maintenance / Run to Fail

Key questions to ask …

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How to start my transformation? Do we have the right team acting?

Business model

(competitive)

Sr. Executive

or LOB Manager

Business Process

(optimization)

Transformation

Team

Process Owner

or IT/OT

Bu

sin

ess

Im

pac

t

Optimize

Business Evolution

Transform

Reimagine

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What are the business opportunities?

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As new

technologies

open doors for

new business

models …

combined teams

with the support

of a design

thinking coach

will …

Is my architecture “IoT ready”? Do I have the right data?

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IoT Platform

Data Storage and Provisioning

Device Management &

Machine Data Integration

Business Process

Integration

Intelligent

Assets

IoT Platform Capabilities

Business

Systems

IoT Application Enablement

Do we have the skills needed?

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Process/Functional/Business Owner

Program Manager / Community Builder

Executive Sponsor

Overall Architect

Data Scientist ExpertData Management / Provisioning Expert

Connectivity / Security Expert

UI Designer / Developer

Analytical Expert

Business

IT/OT

How to start?

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SAP Services – IoT Approach

IoT

Business &

Architecture

Advisory

Services

IoT Platform

– custom

development

services

Application

Mgt and

Education

How will IoT impact my business and architecture?

Which capabilities are required!

How can I run and optimize?

How do I get my IoTscenario up and

running?

Predefined

IoT

Solutions

(Industry &

Cross)

IoT Proof of

Concept &

Starter Kits

Predefined

IoT

Solutions

(Industry &

Cross)

Predefined

IoT

Services

(Industry &

Cross)

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Key Messages

• IoT is not just about technology &products, but transformation

• Lead from the top

• It´s about business, OT and IT. Build a (virtual) team to drive this

• Challenge the E2E process impact potential (“Hand Shake”)

• It is about innovating and ongoing awareness building – start a

data lab

• Enrich your team with needed experts & partners

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Please Visit Our SAP Services IoT Lab

Let´s Start This Journey

Contact information:

Torsten Wolf

EMEA GSS Head IoT & Digital Experience

+4916090822124

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Predictive Quality - Continous Production

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SAP ERP(via QM, PP)

Manufacturing Execution

SAP HANA

PLC1 PLC2

Quality Tests

Defects

Realtime Quality Prediction

in MES for Operator

Data Model (RCS)

Infinite InsightAlgorithms

User Interface

SAP Event Stream Processing(via SAP PCo)

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Failure Pattern Detection: Chemical Company

Company

Solution

Process/Technology Innovation

Benefits

A leading global chemical company

Situation: too many unplanned downtimes of production equipment

• Data historians

• SAP ERP Plant Maintenance

• SAP HANA-based Machine Analytics app

• Automatic analysis of failure patterns

• Early detection of potential future breakdowns

• Improved Overall Equipment Effectiveness

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Connected LogisticsReal-time transportation planning

Transportation

ManagementReal-Time Freight &Truck Visibility

• Fleet usage / availability

• Execution status

• Actual truck positions & planned route

Real-Time Adaptive Planning

• Drag & Drop based

re-planning

• Load optimization

Real-Time DriverCommunication

• Tour update

• Event reporting

• Condition tracking

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Connected LogisticsReal-time transportation tracking & tracing – Cold Chain Monitoring

• Shipment geo location

(onboard unit)

• Shipment status

• Temperature status

(sensor tag)

Condition Tracking

In-TransitMonitoring

• Refrigerated

product shipment

with cold chain

sensor tag and given

temperature ranges

Exception Reporting& Analysis

• Out-of-range temperatures

• Email notification alert

• Event Management status alert

• Map-based event location visualization

• Cold chain analysis and prediction

Track & TraceSAP Event Management

SAP Object Event

Repository

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