Industry 4.0 into PracticeTechnical-, SCM- and Logistic Data integration at KMWE

Marc EversCTO KMWE Group

Koen HerpsProject Manager

Smart Projects19 October 2018

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Content

• Introduction KMWE Group

• BIG Data generation @ KMWE

• Customer needs and trends

• KMWE needs and the link to BIC

• BIC Smart Industries / Industry 4.0

• BIG Data application @ KMWE

• Algorithmization

• Conclusions and Questions

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Introduction KMWE Group

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KMWE contract manufacturing and engineering partner in low volume Parts, Modules or Systems

Part SystemModule

CustomerCustomer Customer

Systems that fit

into 4 to 6 m³

Complex Milling

and Sheet metal

parts. Welded

Structures of

Aluminum,

Titanium, Steel

or Super Alloys,

cubic an

cylindrical

within 1 m³ and

long flat up to

3 m

Modules that fit

into 4 to 6 m³

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Core competences

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Our Markets

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BIG Data @ KMWE

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contract manufacturing businessLow volume, high mix, high tech

Annual volume 50 to 500 parts, modules, systems

Batch size 5 to 15

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KMWE contract manufacturing and engineering partner in low volume Parts, Modules or Systems

Part SystemModule

CustomerCustomer Customer

Systems that fit

into 4 to 6 m³

Complex Milling

and Sheet metal

parts. Welded

Structures of

Aluminum,

Titanium, Steel

or Super Alloys,

cubic an

cylindrical

within 1 m³ and

long flat up to

3 m

Modules that fit

into 4 to 6 m³

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1.00010.000 100

2000

8000

200

800 100

~ 500 supplier ~ 200 supplier

Supply chain activity KMWE group

2500 mat/parts/serv. 10.000 parts/service

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Head Tail company’s

Supply Chain

Tiers

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KMWE Tier 1 / 2

TPD:- M/E Drawings

- Models

- Q reports

- Assembly

instructions

- Specifications

- etc

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Customer needs and trends

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Market Forecast Product Life cycleYears => DATA TPD CYCLE

Average through put time weeks

CLIP (confirm line item performance) days (KMWE Clip 2)

Re-in and outs Max push out period months

interface

A&D Rolling long term (years)

15-30 25 5 2 - 3 portal

M&A Rolling long term (year)

10-20 10 5 1 - 2 Portal and email

Semi F&B Rolling short-term (½ year mounts)

5-10 10 1 12 - 24 portal

S&I Short-term (weeks)

5-10 6 5 2 - 6 email

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Logistic effects re-in or -outs in the supply chain

=> reprioritizing of BIG DATA

Availibility of Technical and Logistics data/information & timely reaction is very critical otherwise

>> inventory >> CASH impact

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KMWE Needs

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Industry 4.0

KMWE agenda is focused on => logistic automation with external interfaces in the chain and Supply Chain Integration

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• Smart Factories– Smart Logistics (24/7)– Flexible factory lay-out– Shared facilities– Sustainability (green, energy neutral)

• Smart Automation– Production automation– Automated handling/loading– Robot & Human interface

• Digital Manufacturing– Smart planning; inventory reduction– 3D Technical data interfaces

(CAD/CAM/QM)– Smart Data interfaces within SC (Portal)– Simulation

KMWE needs

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BIC as a part of the solution

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World

Europe

Eindhoven proximity 200 km

Supply chain integration

BIC

BIC

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Bring the supply chain together into one building:

Optimize data interfaces

Enables analytics and reprioritization

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22

The Smart Factory of High Tech Manufacturing Industry

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Campus of the future

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Factory of the future

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Through the implimenation of Smart Industries projects

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Flexible Manufacturing Advanced Manufacturing Logistics

Smart Connected Suppliers Network

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Use of Big Data fundamental todevelop the Factory of the Future

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Use of Big Data through Algorithmization

High Mix, Low Volume:

• Many different items to be made on 1 machine

High Complexity:

• Tooling storage at machine quickly occupied

Result:

• Lots of toolchanges

High Mix, Low Volume:

• High transportation requirements (int. – ext.)

High Complexity:

• Multi-tenant, prioritazionamong tenants

Result:

• Conflicts, search for optimal transportation solutions

Tooling Supply Chain / transportation

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Use of Big Data through Algorithmization

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Use of Big Data through Algorithmization

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Use of Big Data through Algorithmization

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Use of Big Data through Algorithmization Predict future events and

optimize parameters

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Use of Big Data through Algorithmization

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BIC will help us to optimize (data) interfaces, multi-disciplinary: Prod. Planning, SCM, Work preparation:

- Integrated planning practices; inner- and multicompany

- Optimization of production scheduling

- Sharing facilities @ BIC

- Reduction of transport abundance

Conclusions

Thanks for your attention

Questions?