Hospodářské noviny - Industrie 4.0 Strategický plán...›It has effects over the whole product...

Hospodářské noviny - Industrie 4.0

Strategický plán

Mladá Boleslav

07. Juni 2016

Matthias Rausch, DCoC IT & Prozesse

© Ingenics; Datei: 9050197_ICP_Industrie40_VM.pptx; Name: MRA; Erstellt: 2016-05-13; Gedruckt: 10.06.2016; Version4.0: 1; Status: A; Seite: 1

Agenda

1 Ingenics AG

2 Forth Industrial Revolution – Revolution or Evolution?

3 I4.0@Ingenics

4 Industry 4.0 Strategy Roadmap Example

5 Conclusion

6 References in Czech Republic


› University of Applied Sciences Ulm – Production Technology

› University of Applied Sciences Neu-Ulm – Business Administration; Logistic Management

› Founded in 1979

› 35 years of project experience

› More than 5.300 projects

› 420 employees

› Owner-managed without external capital

› Vendor independent

University Cooperation

Awards

Best Consultant

Ingenics has been

named one of the

best consultancies

Seal of Excellence Education

and Talent Management

TOP Employer

First Place: Overall Ranking

Oliver Herkommer

Chief Executive Officer

(CEO)

Carlos Schmidt

Chief Financial Officer

(CFO)

Manfred Loistl

Chief Human Resources

Officer (CHRO)

Development and Experience The Board

1.1 The Company


PUEBLA ATLANTA

GREENVILLE

PARIS

TOULOUSE

More information at

www.ingenics.com

SHANGHAI

SHENYANG

ULM

STUTTGART, MUNICH

HAMBURG, WOLFSBURG

HEILBRONN, INGOLSTADT

1.5 On-site Worldwide

PRAGUE

BRATISLAVA


Factory Planning Intra Logistics

1.5 Center of Competence

Industrial Engineering

Operational Excellence

Production

Operational Excellence

Management Systems Assembly

Body in White Quality- and Supplier Management

Supply Chain Management

Ingenics Academy

IT and Processes


Agenda

1 Ingenics AG


3 I4.0@Ingenics


5 Conclusion



2.2 Industry 4.0 - Revolution orEvolution?

The digital transformation towards Industry 4.0 is a profound change for the entire organization:

› It has effects over the whole product lifecycle – from development to service

› In the business models and the business processes, internally and with partners

› But – it can be developed with an evolutionary roadmap

Productdesign

and -development

Production

planning

Production

Engineering Production Service

Geschäftspro

zesse

Geschäftsm

odelle

Mensch Organisation Politics Society Law

© hin255 - shutterstock.com

Technologie

Pro

cess

Busin

essm

odell

Human Organization

Technology

Product


Agenda

1 Ingenics AG


3 I4.0@Ingenics


5 Conclusion



3 I4.0@Ingenics

Factory 4.0

Smart Factory

ERP – MES – PLM

Lean Data Management,

Data Security

Strategy Roadmap

Industry 4.0

I4.0@Ingenics

Logistic 4.0 Production 4.0 Assembly 4.0 - MRK

© ArnoMassee - iStockphoto.de

New

Production technologies

Labour 4.0 Big Data


Agenda

1 Ingenics AG


3 I4.0@Ingenics


5 Conclusion



4 Beispielhafte Industrie 4.0 Strategie Roadmap

Strategy Roadmap

› Business Modell

› Organization

› Process

› Product

Big Data

› Business

Intelligence

› Advanced

Analytics

Manufacturing

Execution System

Human Robotic

Collaboration

Big Data

› Predictive

Maintenance

wavebreakmedia/Shutterstock.com, asharkyu/Shutterstock.com


4.1 Industry 4.0 – Approaches for Strategy development

No matter which way you decide to use – the important thing is to start.

Industry

4.0

Strategy

› Industry 4.0 Concrete

› Process Maturity

› Technology

Quick Check

› Business Modell

Development


4.2 Real-time MES

Increase of production efficiency by implementation of a shop floor

Management system

Task:

Automotive Supplier Industry:

› Production processes driven by paper

› Confirmations with a time delay

› No direct information on machine status

Basis:

› Definition and tender for a Manufacturing execution system

› Implementation of the FORCAM system

› Graphical real-time production cockpit

› All confirmations from 350 employees digitalized

› Automated and manual MDE Integration, depending on machine

capabilities

› Real-time machine information over secured wireless infrastructure

› Real-time SAP integration triggered by events

› Use of Industry clients, Barcode and RFID to increase usability

Approach:

Result:

› Increase machine efficiency by 25%

› Increase worker efficiency by 3%

within three month

› Decrease of energy costs by 10%

› Return on invest realized within

three month

© FORCAM GmbH


4.2.9 OEM – (BI) Customer Analytics

Results:

› View customer concerns across

multiple systems in Qlikview

Application.

› Manual classification of

customer survey comments

replaced by a machine learning

auto-categorizer

› Auto-categorizer achieves 90%

accuracy

› Reduction of classification time

from 2 weeks to minutes

Development Early Intervention Recognition

System

Task:

Automotive OEM Manufacturer Industry:

› This application facilitates cross correlation of

emerging customer satisfaction and safety issues over

vehicle’s lifetime which will augment senior

management in decision making process, in order to

increase owner loyalty and reduce negative media

exposure.

Basis:

› Data integration & ETL of CFS, NHTSA, IQS & Other

relevant data sources in one Big Data Lake

› Using VFC(Vehicle Fault Codes) to classify customer

comments with an automated machine learning

algorithm

› Visualize results in Qlikview app with possible drill

downs & filters for gaining data insights

› Development of predictive algorithms in R and Python

› Investigated >20 algorithms and library for solving the

problem. SVM performed best!

Approach:

© ra2studio/Shutterstock.com


4.4 OEM – Realization Human-Robotic Collaboration (MRK) in Assembly

Task: Define concept for a Human Robotic Collaboration

Industry: Automotive OEM

Results:

› Pilot area defined

› First pilot Implementation in

assembly realized

› Planning and Implementation of

further collaboration workplaces

› New production technologies should be introduced to workers

› Evaluation of possible areas for robotic support without safety cases

Approach:

› Definition of evaluation criteria

› Systematic analysis of the band portions BA 0, 1, 2, 3, door mounting,

cockpit installation, door installation regarding possible applications against

the evaluation criteria

› Classification of possible MRK-use fields

› Roadmap with presentation of applications sorted by probability of

realization over time

› Development of concepts

› Derivation of fields for an "assembly of the future"

Basis:


4.2.12 OEM – (BI) Predictive Maintenance Body Shop

Tool to steer maintenance activities to reduce

Body Shop downtime

Task:

Automotive OEM Manufacturer Industry:

› The goal of this production line analysis is to

determine a correlation between a piece of

equipment’s current performance and future failure.

The focus for the pilot implementation will be on

equipment measures from the body shop. Expected

results are to find a trend with a machine‘s

performance prior to failure.

Basis:

› After merging different data sources, derivation of new

variables, feature selection of relevant variables (e.g.,

fault codes), and anomaly detection, various

prediction models will be built to establish a

confidence of on coming equipment failure.

› Development of predictive models with Python

› Data visualization with iPython notebooks and Bokeh

Approach:

Results:

› Ongoing POC with targeted

completion in 2016

› Control Charts & Other

Visualizations for downtime

trend visualizations

› Integrated sensor data with

other data sources for better

root-cause identification

© ra2studio/Shutterstock.com


Agenda

1 Ingenics AG


3 I4.0@Ingenics


5 Conclusion



5 Conclusion

There will be no stable Industry 4.0 plant model. Due to the rapid development of technology, companies

have to get more agile to adopt technology and adjust their processes on a regular level.

› It’s no a question of “IF”, but of “HOW” – Solutions have to be

created individually for each company.

› There are no extensively solutions available yet. Go for specific

solutions, which both fulfill current needs and future requests

› It is not about “Google glasses”. Technology just creates

business value if it’s use is harmonized with the organization and

the processes.

› If you start Industry 4.0 project, be aware to lean your process

landscape. Lean methods can be used in indirect departments as

well. Only with a combined approach you will realize real

business values.

› Each project has to have a clear goal.


Without knowing your goals and your current situation, you can not choose the right way.

The definition of your individual, sustained and successful strategy roadmap should have

highest priority.

Start today – Get ready for Industry 4.0

5 Conclusion


Agenda

1 Ingenics AG


3 I4.0@Ingenics


5 Conclusion



› VW Koncern – Skoda Auto, Ml. Boleslav

› Bombardier, Liberec

› ZF, Pilsen

› Schott, Val. Mezirici

› F.X. Meiller, Slany

› GEA LVZ, a.s. , Liberec

› Ciret , Pelhrimov

› arvato - services , Stochov


Díky za váše pozornost.

Prosím váše otázky. Your personal contact

Ingenics AG · Schillerstraße 1/15 · 89077 Ulm · Tel. +49 731 93680 0 · [email protected] · www.ingenics.de

Matthias Rausch

Dipl. Wirtschaftsmathematiker Director Center of

Competence IT und Prozesse

[email protected]

+49 151 10849361

Udo Richter

Dr. rer.nat. Director Sales

[email protected]

+420 605 343 091

Hospodářské noviny - Industrie 4.0 Strategický plán...›It has effects over the whole product...

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