Digital Transformation and IIOT at Siemens

Digital Transformation

and IIOT at SiemensPatrick Riordan and Edward Kovanda

siemens.com

2020-02-19Page 2 Dr. Patrick Riordan & Edward Kovanda / IOT Consulting

What we are sure

you already know

This is not

SIEMENS

This is also not

SIEMENS

And maybe

surprising

This also not

What you probably

also know

This is

SIEMENS

This is

SIEMENS

This is

SIEMENS

This is

SIEMENS

This is

SIEMENS

This is

SIEMENS

What you probably do not know

This is also

SIEMENS

• 50+ Digi Labs and AI Centers around the globe (also in Munich)

• 500+ data scientists in Germany, 200+ in Munich

• Thought leader in Responsible AI (Charter of Trust, DIN Normungsroadmap KI)

• Filed 2,493 European patents in 2019 (more than any other company), 25% in industry 4.0

and digitalization

• Corporate startup incubator Next47 with 20+ companies in the portfolio and 1bn € to invest

Innovation happens in all

core technology areas

CM5: MI Core

CM4: Automated digitalization of domain knowledge

CM1: AI on the edge & distributed AI

CM8: AI-driven enterprise

CM6: Artificial Engineer

415763

Longer term Short term

878889

120130

121131

161171

153163

115135

148 158

CM2: Empower non-experts to use DA

174125

CM7: Digital companion

3050180 144

203 204

CM3: Self-X

216214

215213

We are IoT Digital Consulting

We are

+50021 10consultantsoffices countries

7,000developers & engineers

… to 1000s of renewable in-feed

And accompany our customers

From few central power plants …

… to data-driven predictive maintenance

From manual diagnostic-based maintenance …

… to real time online monitoring

From periodic manual meter readings …

Main question for today

To be able to be a leading player in this field, Siemens has

transformed itself towards a software company

What is it like to do data science

at Siemens IoT today?

Big to smart data

Big data vs. smart data

2000s Big Data ResultArtificial

Intelligence

Big Data ResultArtificial

Intelligence

Big Data

Domain

Knowhow

Intelligence

Big Data

Smart Data

Domain

Knowhow

Intelligence

Big Data

Smart Data ResultArtificial

IntelligenceDomain

Knowhow

Skill #1: Work with the experts

To be able to be a leading player in this field, Siemens has

transformed itself towards a software company

The cloud and the edge

Skill #2: Select the right technology

Black Box vs. XAI

“Asking for interpretability as a condition for

real world usages is undermining the

foundations of the whole field. If the trained

model has good performances and it’s not

interpretable we are probably on the right track;

if it’s interpretable (and the explanation is

understandable and replicable) why loosing

weeks and GPU power? Just write some if-else

clauses.”

Massimo Belloni, Data Scientist at HousingAnywhere

in his medium post from April 30th, 2019,

"If it's interpretable, it's pretty much useless"

“AI systems and their decisions should be

explained in a manner adapted to the

stakeholder concerned. Humans need to be

aware that they are interacting with an AI

system, and must be informed of the system’s

capabilities and limitations.”

European Commission High-Level Expert Group on AI

in their "Ethics Guidelines for Trustworthy AI"

from April 8th, 2019,

Skill #3: Select the appropriate model

Let's put this to practice

Sand and Dust prediction

Skill #1What do I know about Sand? How often do pathways get blocked? How critical is it really?

Skill #2Who exactly and how is our customer going to be working with our solution?

Skill #3 How critical are prediction results? Life-and-death situation for involved humans? State regulated?

YYYY-MM-DDPage 46 Author / Department

Don’t forget

the experts

Have the end

user in mind

Sexy doesn't

always win

“When considering how IoT can transform your

organization, remember that the business is

more important than the technology. The

technology might be exciting and new, but it

must serve the business, not the other way

around. When investigating the ROI of an IoT

initiative, the IoT solution determines the invest,

and the business problem determines the

potential return.”

Siemens IOT Services

in their whitepaper (in print)

"Introducing IOT pays off – fact or fiction?"

Any questions?

Contact us!

Dr. Patrick Riordan

IoT Consulting

Digital Consulting

Data Analytics

riordan.patrick@siemens.com

Edward Kovanda

IoT Consulting

Digital Consulting

Data Analytics

edward.kovanda@siemens.com

siemens.com

Digital Transformation and IIOT at Siemens

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