CONVANIT

SMART automation & analysisSteffen Pröhl, Michael Meinel

@Systema Expert Day

January 2018

C O N VA N I T

CONVANIT

Smart Factory

“The Smart Factory will

be much more

intelligent, flexible and

dynamic.”

2 January 2018

• Manufacturing processes will be organized differently, with entire production chains – from suppliers

to logistics to the life cycle management of a product – closely connected across corporate boundaries.

• Individual production steps will be seamlessly connected. Production runs autonomously.

• In a Smart Factory, machinery and equipment will have the ability to improve processes through self-

optimization and autonomous decision-making.

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CONVANIT

Smart Factory characteristics

5 major features:

connectivity,

optimization,

transparency,

proactivity and

agility

3 January 2018

Source: IOSPress

CONVANIT

Smart Factory components

Key Messages:

• the technology is (mainly) there already. For sure

there are still technical challenges to be resolved

(security, platforms open to „everything“) - but this is

no blocking point.

• People have to go along with all this new technology

– it is about the daily usage of the capabilities given

4 January 2018

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CONVANIT

Smart Factory

… needs SMART Automation

1. Starting small and scaling

– to unlock value

2. Distinction between real

technical automation issues and “health” features

3. Prioritization of automation requirements / automation projects according to the “value” question

4. It’s an organizational thing!

5. Its all about …people

5 January 2018

Sou

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sis.

A Smart Factory – needs Smart Automation and customizing to goals and needs: What needs to be done with the data to create the most value.

CONVANIT

How to create the most value?

• How do we become SMART?

• What do we do with all the data?

• What does it mean to each individual

in the organization?

6 January 2018

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CONVANIT

To become smart(er)…

…we first need to define the questions.

“If I had only one hour to save the world, I would spend fifty-five minutes to

define the problem, and only five minutes to find the solution.“

Albert Einstein

7 January 2018

CONVANIT

It’s all about interactions.

„Data Mining is the non-trivial process of identifying valid, novel, potentially

useful and ultimately understandable patterns or structures or models or

trends or relationsships in data to enable data driven decision making.“

Diego Kuonen, Data Scientist

8 January 2018

To become smart(er)…

CONVANIT

For data driven decision making we need

indepth knowledge of our processes,

analytical skills and

data analysis capabilities.

9 January 2018

To become smart(er)…

CONVANIT

What to do with all the data?

Fields of Use TODAY(semiconductor industry)

Statistical Process Control

Feed forward / feedbackward control (R2R)

Fault Detection & Classification

Preventive/PredictiveMaintenance

Virtual Metrology

Process Characterisation

Yield Learning

Defect Learning

Machine Learning

Data Stores

Maintenance data,

Diagnostic data,

Trace/Sensor data

Process Control data

Metrology data

Tool Log data

Facility data

WIP Tracking data

Yield data

Defect data

FUTURE

Holostic approach:

Capability to analyse by

combining any data.

Permanent, flexible and

fast

realization/implementation

of use cases.

10 January 2018

CONVANIT

What to do with all the data?

Technologies for data storage today:

Goods and bads

Relational Databases + Common for structured data- Not suited for large data sets of time series data

Optimized Systems(e.g. Hadoop)

+ Very well suited for large amounts of data and complex queries+ Partly with SQL interfaces

Time Series Databases + Very good performance for time series data- Often propriatary interfaces

In-Memory databases + Very good performance for all data which can be stored In-Memory- Only for high-performance hardware, complex queries

NoSQL databases + Fast software engineering+ Data structure offers high flexibility- Often propriatary interfaces

Hybrid databases + Combination of relational data, time series and noSQL data+ Easy combination of different data structures+ SQL and NoSQL interfaces

11 January 2018

CONVANIT

What to do with all the data?

Data analysis requirements of the future

• Fast import and fast processing of large amounts of data

• Use of different data types and structures (structured to unstructured)

• Processing of a large number of ‚columns‘ within a dataset

• Realtime Processing

• Short response time by complex queries

• Concurrent Queries

• Connectivity across data stores

Capability to analyse by combining any data.

Permanent, flexible and fast realization/implementation of use cases.

12 January 2018

CONVANIT

What does it mean to us?

What needs to be discussed:

How do you imagine an IT infrastructure in 10 years, which fullfills the

requirements for data analysis?

Capability to analyse by combining any data.

Permanent, flexible and fast realization/implementation of use cases.

Which conflicts do you see to other requirements of smart

automation?

13 January 2018

CONVANIT

Further questions:

please contact:

steffen.proehl@CONVANIT.com

michael.meinel@CONVANIT.com

www.CONVANIT.com

technical CONsulting for adVANcement including IT