zum Thema Industrie 4.0 Industry Robert Rudolph Member of the - - PowerPoint PPT Presentation

1 | Swissmem Executive Seminar, 27. Mai 2016

Verständnis und Aktivitäten von Swissmem zum Thema Industrie 4.0

Industrie 4.0 – A Chance for the Swiss Industry

Robert Rudolph Member of the Board Swissmem / President Industrie 2025

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Agenda

• Initiative «Industrie 2025»
• Understanding of Industrie 4.0
• Examples / Use Cases

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Examples of Products

• Ma

Machi hiner ery  Machine tools, textile machinery  Pumps, compressors  Turbines  Packaging & filling machines

• Preci

recision ion Inst strume uments ts  Tools  Medical Instruments

• Elec

lectronic

• nics

 Electrical switches and cables  Electrical drives  Control equipment & sensors

• Me

Metals ls

• Vehic

hicles es

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www.industrie2025.ch @Industrie2025

• inform
• raise awareness
• network
• promote

Su Supp pport (on-site workshops, seminars, basic training) Innov

• vat

ation ion su supp pport (R&D Conference, coordination) Technic nical al to topi pics cs (working groups, whitepapers, studies) Netw etwork rking ing and know

• wledg

ledge tran ransf sfer (events, seminars)

National Initiative for Industrie 4.0

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History of «Industrie 4.0»

2012 2012 January: Working Committee «Industrie 4.0» (acatech) April: First presentation on «Industrie 4.0» @ HMI 2013 2013 April: Presentation of final report of WC to Chancellor Merkel @ HMI, Launch of «Zukunftsprojekt Industrie 4.0» June: Start of Plattform Industrie 4.0, Start of working groups, lead by VDMA, BITKOM and ZVEI 2014 2014 Industrie 4.0 is main topic @ CeBIT and HMI 2015 2015 @ HMI BMWi (Gabriel) and BMBF (Wanka) take over leadership of Plattform Industrie 4.0 2016 2016 VDMA-Forum Industrie 4.0: Pathway to networked production

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International Activities

• Germany: Plattform Industrie 4.0
• Netherlands: Smart Industry
• Schweden: Produktion 2030
• France: Usine du Futur
• USA: Industrial Internet Consortia (IIC)
• China: 物联网 (wù lián wăng)
• Austria: Industrie 4.0 Österreich

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Digital Transition in Industry

Automatisation Electronics (3. Revolution) Intelligent Value Chains (4. Revolution)

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Basic Understanding

Optimization of pro roduct uction

• n

equipmen ent, proc

• cesses

ses up to cross-company value ue add added chain ains Digitalization of pro roduct cts, servic ices es and their Life fe cycle ycles Increase of productivity and agility Innovationen for the market (customer value) New business models Us User ers Su Suppl pplier iers

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9 | Swissmem Executive Seminar, 27. Mai 2016

Cros ross-secti ctional

• nal

techno nologi logies

Opportunities for «Use Cases»

Product Machine Production ERP Cloud Horiz izontal

• ntal Integ

egrat ation

• n

Vertic tical al Integ egrat ation

• n

Integ egrat atio ion n of f Eng ngineering ering Value ue Add dded Ch Chai ain Life fe cycl ycle ERP, PPS, MES + PLM, PDM Us Use Cas ase

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«Use Case» have a range of aspects

«Use Cases» are a combination of:

• Technologies
• Data
• Processes
• Methods / Models
• Services
• Safety / Security
• Standards

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Large field of technologies

Production Technologies Production Planning Production Control (System) Simulation Robotics Digital Engineering Visualization Sensors Actuators Vision Systems Wireless Communication Augmented Reality ICT Architecture Identification Technologies Big Data Artificial Intelligence Pervasive Computing ICT Security Data Safety Resilient ICT Assistence- Systems Innovation Methodology Labor 4.0 Digital Business Supply Chain Digital Life Cycles

* Not complete

Additive Manufacturing

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Internet of Things

11

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Use Case: Connected Factory

Prev reven ention ion of defic eficenc encie ies in assembly

• Unplanned situations are detected

and handled by the system

• Product is guided through assembly
• Cooperation of smart automatisation

with cognitive and creative skills of workers

Bild: Demag Cranes

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Use Case: Market Place Application Know-how

Access to internal and external application and technology know-how allows to optimize machine tool

• peration in terms of quality,

, time me and and effic icie ienc ncy

• Application data from archive
• Cross-machine logging and

evaluation of operation and condition data

• Comparison with manufacturer data
• Business model on public market

places

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Use Case: Condition Monitoring

Lenses are consumables in laser machine tools

• Identification of lenses
• Diagnosis system evaluates

specification of lens

• Measurement/Calculation of wear

buffer

• Recording history

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Example: Pilot Line Bosch Rexroth

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Six basic types of disc valves in 200 variants  Enhanced assistance systems

MES PPS Equipment Man Communi- cation Product

15

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Example: Digital Engineering for Faucets

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Where is the biggest benefit of Industrie 4.0?

Percentage of companies / multiple answers allowed

Individualised Products Flexible Production Stronger Customer Relation Resource / Process Efficiency Increase in Product and Service Quality New Customer Value Increase of Productivity

0% 10% 20% 30% 40% 50% 60%

82% of the respondents see one or multiple benefits in the concept Industrie 4.0

Source: Swissmem Survey May/June 2016

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Status of Project Implementation

Percentage of companies/ multiple answers allowed

43% 55% 44% 63% 82%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% geplante Projekte laufende Projekte umgesetzte Projekte Potenzial für eigene Projekte: KMU Potenzial für eigene Projekte: alle Unternehmen

Source: Swissmem Survey May/June 2016

Amongst the respondents 1‘225 projects are implemented, running or planned. Of those 718 are with SME.

Potential in own company: all respondents Potential in own company: SME only Implemented Projects Ongoing Projects Planned Projects

19 | Swissmem Executive Seminar, 27. Mai 2016

What are the biggest obstacles?

Percentage of companies / multiple answers allowed

Missing holistic strategy on Industrie 4.0 Missing personel resources Missing understanding

• r incomplete

conception of subject

0% 10% 20% 30% 40% 50% 60%

Source: Swissmem Survey May/June 2016

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Some Thoughts on Data

• «Data is the new oil»  Transparency  Control
• Fundamental for new (digital) business models

Use of publicly available data Models from web world probably not applicable in industry

• Interpretation of data in manufacturing context
• Modelling / Semantics
• Data rights / trade secrets / trust / personal data protection

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Take the Challenge!

Watc tch Vis isio ionar ary

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