Hospodářské noviny - Industrie 4.0

Transcription

Hospodářské noviny - Industrie 4.0
Strategický plán
Mladá Boleslav
07. Juni 2016
Matthias Rausch, DCoC IT & Prozesse
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
© Ingenics; Datei: 9050197_ICP_Industrie40_VM.pptx; Name: MRA; Erstellt: 2016-05-13; Gedruckt: 10.06.2016; Version4.0: 1; Status: A; Seite: 1
1.1
The Company
Development and Experience
›
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›
›
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The Board
Founded in 1979
35 years of project experience
More than 5.300 projects
420 employees
Owner-managed without external capital
Vendor independent
Carlos Schmidt
Chief Financial Officer
(CFO)
Manfred Loistl
Chief Human Resources
Officer (CHRO)
Oliver Herkommer
Chief Executive Officer
(CEO)
University Cooperation
› University of Applied Sciences Ulm – Production Technology
› University of Applied Sciences Neu-Ulm – Business Administration; Logistic Management
Awards
Best Consultant
Ingenics has been
named one of the
best consultancies
TOP Employer
First Place: Overall Ranking
Seal of Excellence Education
and Talent Management
1.5
On-site Worldwide
PUEBLA
ATLANTA
GREENVILLE
PARIS
TOULOUSE
ULM
STUTTGART, MUNICH
HAMBURG, WOLFSBURG
HEILBRONN, INGOLSTADT
SHANGHAI
SHENYANG
PRAGUE
BRATISLAVA
More information at
www.ingenics.com
1.5
Center of Competence
Factory Planning
Intra Logistics
Industrial Engineering
Supply Chain Management
Assembly
Operational Excellence
Management Systems
Body in White
Quality- and Supplier Management
Operational Excellence
Production
IT and Processes
Ingenics Academy
Agenda
1 Ingenics AG
3 I4.0@Ingenics
5 Conclusion
Industry 4.0 - Revolution orEvolution?
Productdesign
Product
and -development
Production
planning
Production
Engineering
Production
Service
Geschäftsmodelle
Businessmodell
Geschäftsprozesse
Process
2.2
© hin255 - shutterstock.com
Technologie
Technology
Mensch
Human
Organisation
Organization
Politics
Society
Law
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
Agenda
1 Ingenics AG
3 I4.0@Ingenics
5 Conclusion
3
I4.0@Ingenics
Strategy Roadmap
Industry 4.0
Logistic 4.0
Production 4.0
Assembly 4.0 - MRK
© ArnoMassee - iStockphoto.de
Factory 4.0
New
Production technologies
I4.0@Ingenics
Labour 4.0
Lean Data Management,
Data Security
Smart Factory
ERP – MES – PLM
Big Data
Agenda
1 Ingenics AG
3 I4.0@Ingenics
5 Conclusion
4
Beispielhafte Industrie 4.0 Strategie Roadmap
Manufacturing
Execution System
Big Data
›
Business
Intelligence
Strategy Roadmap
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Advanced
Analytics
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Business Modell
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Organization
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Big Data
Process
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› Predictive
Product
Maintenance
Human Robotic
Collaboration
wavebreakmedia/Shutterstock.com, asharkyu/Shutterstock.com
4.1
Industry 4.0 – Approaches for Strategy development
› Technology
Quick Check
› Industry 4.0 Concrete
Industry
4.0
Strategy
› Process Maturity
› Business Modell
Development
No matter which way you decide to use – the important thing is to start.
4.2
Task:
Industry:
Real-time MES
Increase of production efficiency by implementation of a shop floor
Management system
Automotive Supplier
Basis:
› Production processes driven by paper
› Confirmations with a time delay
› No direct information on machine status
Approach:
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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
© FORCAM GmbH
Result:
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Increase machine efficiency by 25%
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Increase worker efficiency by 3%
within three month
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Decrease of energy costs by 10%
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Return on invest realized within
three month
4.2.9
OEM – (BI) Customer Analytics
Task:
Development Early Intervention Recognition
System
Industry:
Automotive OEM Manufacturer
Basis:
› 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.
Approach:
› 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
© ra2studio/Shutterstock.com
Results:
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› Visualize results in Qlikview app with possible drill
downs & filters for gaining data insights
› Development of predictive algorithms in R and Python
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› Investigated >20 algorithms and library for solving the
problem. SVM performed best!
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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
4.4 OEM – Realization Human-Robotic Collaboration (MRK) in Assembly
Task:
Define concept for a Human Robotic Collaboration
Industry:
Automotive OEM
Basis:
› 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"
Results:
› Pilot area defined
› First pilot Implementation in
assembly realized
› Planning and Implementation of
further collaboration workplaces
4.2.12 OEM – (BI) Predictive Maintenance Body Shop
Task:
Tool to steer maintenance activities to reduce
Body Shop downtime
Industry:
Automotive OEM Manufacturer
Basis:
› 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.
Approach:
› 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
© ra2studio/Shutterstock.com
Results:
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Ongoing POC with targeted
completion in 2016
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Control Charts & Other
Visualizations for downtime
trend visualizations
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Integrated sensor data with
other data sources for better
root-cause identification
Agenda
1 Ingenics AG
3 I4.0@Ingenics
5 Conclusion
5
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Conclusion
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.
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.
5
Conclusion
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
Agenda
1 Ingenics AG
3 I4.0@Ingenics
5 Conclusion
6
References in Czech Republic
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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
Matthias Rausch
Dipl. Wirtschaftsmathematiker
Director Center of
Competence IT und Prozesse
Udo Richter
Dr. rer.nat.
Director Sales
[email protected]
+49 151 10849361
[email protected]
+420 605 343 091
Ingenics AG · Schillerstraße 1/15 · 89077 Ulm · Tel. +49 731 93680 0 · [email protected] · www.ingenics.de

Hospodářské noviny - Industrie 4.0

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