Industry 4.0 in a Nutshell What is really new? · • Internet Banking • Flight and travel...

Industry 4.0 in a Nutshell – What is really new?

7th International Conference on Virtual Machining

Hamilton, Ontario, 7 – 9 May 2018

Michael F. Zaeh, Prof. Dr.-Ing, TU Munich, Germany

(Institute for Machine Tools and Industrial Management)

Michael F. Zaeh, Prof. Dr.-Ing.

© iwb – Institute for Machine Tools and Industrial Management

The Digital Shadow and Data Acquisition2

Definitions, Enablers, Benefits, Opinions1

Agenda

2

5

4

3

Industry´s Position and Approach

Artificial Intelligence – two Examples

Additive Manufacturing is Part of it

6 Recommendations and Summary





Agenda

3

5

4

3







Definitions, Enablers, Benefits, Opinions

4

Industry 4.0 is an initiative of the Federal German Government in cooperation with Industry, which

is striving to secure Germany´s top position by empowering it with respect to digital tools and methods.

A major goal is the Smart Factory, which is characterized by changeability, resource efficiency,

ergonomic design as well as integration of business partners in the processes.

The term was introduced in 2011 during the Hanover Trade Show. In October 2012 the Federal

German Government introduced recommendations concerning Industry 4.0.

To bring it to the point:

Use of networked systems of all kinds within and between factories as well as towards customers

and suppliers (Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS))

The connected mode (Internet of Things, Internet of Everything) allows for the accumulation of data

on a large scale and for the extraction of certain patterns (Big Data), also for new business models.

Industry 4.0

© iwb – Institute for Machine Tools and Industrial Management 6

Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS)

are main elements of Industry 4.0. (= Mechatronic systems, which communicate via a

data infrastructure, for example the Internet) - Internet of Things (IoT).

CP(P)S dominate future production and logistics scenarios as

…intelligent products and

…intelligent production equipment.

CP(P)S in production connect themselves ad-hoc and thus allow for

…decentralized, highly reactive control systems,

…the increased use of decentralized intelligence,

…situation dependent control structures as well as

…an effective integration of people in production.

CPPS interact with intelligent CPS-products; CPS as a device in production

Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS)



Added value in production because of Industry 4.0

7Sources: Working group on Industry 4.0., acatech,Weyrich

Increase of flexibility

Smarter integration of the

workforce

Efficient use of resources

Reduced time to market

Improved competitiveness

Powerful SCM

Reduced peak loads

Customer requirements better

taken care of

Internet of Services

Internet of Things

It is nothing but CIM reloaded.

Those who master it have a competitive edge.



CIM = Computer Integrated Manufacturing (1980ies/90ies)

8

Aufträge

...

157030

100

Order ProductSale

ssyste

m

CAQ

FLS

BDE

SCM

DNCNC /

CNC

SPS

Sh

ipp

ing

syste

m

ERP / PPS

Qualityfeatures

Parts list

Desig

n

Geometry

NC-program

Internal

orders

Wo

rk p

lan

Qualityinformation

Qualityinformation

Technology/Process

Pla

nn

ed

ord

er

Purchase ordersScheduling

Shop

floor data

Part

s lis

t

Work

plan

Qualityinformation

Suppliers

EDI / www (XML)

Customer

PDM

Shop

floor data

NC

-pro

gra

ms

co

ntr

ol

co

mm

an

ds

CAP

CAM

CAD

CAE



The digital twin/shadow from the supply chain all the way to the processes

Cyber-Physical Systems allow the synchronization and merging

of the real and the virtual world.

Real-time disturbance management

Task-oriented programming

Virtual commissioning

Discrete event simulation

The digital shadow

Network

Machine control

Process control

Production planning and scheduling

Real world

On the way to Industry 4.0



Where do we stand today?

10

The ideas are not new. However, today we have a better technological basis.

Expert opinions concerning the Status quo and concerning the achievability differ considerably, from …

Source: Gerhard Volkwein

Everything exists

already!

… up to …

Completely utopian!



The idea of Industry 4.0 has already infiltrated our daily routine.

11

Past Present

• Money transfer via a written check or money

order

• Travel agencies

• Ticketing at a counter

• Purchase in stores

• Telephone book

• Car purchase

• Internet Banking

• Flight and travel booking through internet

(booking.com, hrs.com, …)

• Ticketing via

Web-Page and credit card

• Purchase via Internet

(Amazon, Zalando, …)

• Internet phone book

• Car sharing

“Industry 4.0“ has reached the private sector a long time ago.

• Programming of web-interfaces

• Clarification of organizational and legal

aspects

(returns, cancellations, …)

• Web-security as a permanent task





Agenda

12

5

4

3







Simulation of the Thermal Behaviour / How to get to the Model Quickly

13

Software tool for semi-automatic creation of a thermal model …

transforms mechanical models into thermal models including …

definition of the constraints (conduction, convection, radiation).

Mechanical

modelThermal

model

constraints

location

amount

NC cycles

The Digital Shadow and Data Acquisition


Standardized Interface Between Tool and Machine for Data and Energy Transfer

14Source: BazMod - Bauteilgerechte Maschinenkonfiguration durch Einsatz von CPS

(Workpiece conformal machine configuration via CPS)

Motivation and goal

• Currently time and cost intensive integration of

CPS in machine tools

• Idea of the USB-interface: Plug & Produce

Approach

• New industry specific interface for energy and data

transfer into and from rotating systems

• Design such that retrofit is possible

• Software architecture for the integration of the CPS

into a machine tool control system

Contactless energy and

data transfer via

induction

Ultra sonic actuator

Interface to the spindle

Milling tool

The Digital Shadow and Data Acquisition




Agenda

15

5

4

3








The powder bed based Additive Manufacturing …

16

3D-CAD-modelSTL-file

Support generation

and virtual slicing

Repetitive

layer creation

Workpiece

Layer deposition

Layer solidification

platform lowered by the

thickness of one layer

Process preparations

Finishing

Source: SLM-

Solutions GmbH

Quelle: Deckel-Maho

… is characterized by a completely integrated process chain.

http://www.sg-zerspanung.de/images/maschine02.jpg

http://www.sg-zerspanung.de/images/maschine02.jpg


External reamers require high precision

(e.g. for valve spool finishing)

Lightweight design is good for dynamic behaviour

Laser Beam Melting (LBM) of titanium and steel alloys

Approach:

TiAl6V4 as standard alloy for lightweight applications

1.2709 (X3NiCoMoTi18-9-5) as standard steel alloy

SLM 250HL machine, 400 W YLR-fibre laser

Motivation:

Results:

Process was adopted by industrial partner Mapal

(with further development)

Approximately 54 % mass reduction resulting in

lower vibration amplitudes during the machining

process

Integrated Cooling

Lubricant Channel

Lightweight

Structures

Conventional

Design

Lightweight

AM-Design

Lightweight

AM-Design

(finished)

Additive Manufacturing of a Reamer (reaming tool holder)


Source: Fraunhofer IWU/IGCV


Additive Manufacturing of Gears

18

Lightweight design und functional integration is also increasing

in gear manufacturing using case hardening steels

Laser beam melting of case hardening steels

Approach:

Reference alloy: ASTM 5115 (16MnCr5)

EOS M270 machine,

beam source: 200 W Ytterbium fibre laser

Process sequence: stress relief annealing, case

hardening, hard finishing

Motivation:

Results and outlook:

Average mass reduced by 25 %

conformal cooling for high temperature transmission

Shorter lead times and process sequences

Integrated

cooling

channelsLoad-adapted

biomimetic structures

Sources: Stahl, Kamps, Fraunhofer IGCV



Geometrical Features are for free, because …

Sources: Fraunhofer IGCV, iwb

… the manufacturing costs of a part are not determined by the features, but

predominantly by the part volume.


19

Temp. in °C


Topology Optimized Osteosynthesis Plates

mandible

fibula segments

topology optimized

implant Asubtractive manufacturing

(milling)

design space Badditive manufacturing without post-processing

(Electron Beam Melting EBM)

design space Cadditive manufacturing with post-processing

(Electron Beam Melting EBM)


23

© iwb – Institute for Machine Tools and Industrial Management 21Source: DMG Mori

Hybrid Approach Integrating Additive and Cutting Technologies


Laser Cladding Laser Cladding Milling

DMG Mori Lasertec 65 3D (also on www.youtube.com)

Laser Cladding Milling




Agenda

22

5

4

3








An Evolutionary Algorithm in Job Order Planning

23

Decription of the Initial Situation: Assembly of Household Appliances (Dish Washers etc.)

Manual planning of the job order sequences based on input (forecast) from sales and distribution

8 assembly lines with different capacities and capabilites; high set-up costs when changing from one batch/lot to another

Manual optimization not possible due to high number of solutions, constraints and interdependencies

Dealer order triggers delivery

Distribution

centre

Dealer /Outlet

Orders by

fax, telephone, Internet

Feedback

loop 1

RegionalWarehouse

48 h-Service

FactoryWarehouse

Supplier

Supplier

Supplier

OEM´s Factory

Feedback

loop 2

MRP / Materials Management

• Aggregation an review of

sales planning figures

• Capacity planning

• Assembly planning

• Procurement

Regional planning

• Top-down sales planning

(total numbers, model groups)

• Bottom-up sales planning

(particular models)

• Iterative processing

Production Distribution




24

Decription of the Initial Situation: Assembly of Household Appliances (Dish Washers etc.)

Manual job order planning for the next day on the basis of set-up codes

(indicating similarities among the models and thus in set-up and line requirements)

Day i Day i+1

Filling up

the capacity

of a day

-

Dispatching

of orders

to lines

L 1

L 2

L 3

Line scheduling Sequence optimizationSimilar models are being aggregated

to internal orders and dispatched to lines

Set-up-codes help to group and to minimize

the set-up times, efforts and costs

Assembly batches/lots

100

150 50

Set-up code

Digit-#

1 Model-#

2 Heat exchanger

3 Control

4 Programs

5 Noise reduction

6 Salt sensor

7 …

8…




25

Decription of the initial situation: assembly of household appliances (Dish Washers etc.)

Manual planning on the basis of SAP planning charts

Sequencing done iteratively based on set-up code and experience of the person in charge

(2 hours per day)

Line options

indicated by a

colour code

Dispatching

to assembly lines

via mouse click


Arbitrary initial

population

Artificial Intelligence – two examples


26

Solution

Calculate fitness

for all individuals

Select a number

of the best

individuals as

parents for the

next generation

Create next

generation (partly

randomized)

Check abort

criterion Final result

Selection and

recombination

Mutation and

reproduction

j

n

j jj

n

j

a

i ii xkbGrfitj

*)(11

1

1 1;

j : Index of the assembly line (j = 1,2,…,n)

i : Index of the order on the assembly line j (i = 1,2,…,aj)

: Number of orders on line j

: Costs for changing from order i to order i+1

G: Factor penalizing capacity overload (or other unwanted effects)

bj: Capacity load of line j; kj: available capacity of line j

xj: = 1 for bj >kj , otherwise 0

ja

1; iir




27

Results User interface

In use since 2005

Planning time reduced

from 2 hours to 10 minutes per day

Increased quality of the planning

result (= better fitness)

Reduced costs for material and line use

Increased productivity

… achieved in an

industrial project involving

two PhD candidates

and one student



Artificial Neural Networks and Evolutionary Algorithms to Minimize Welding Distortions

28

Laser Welding induces deformations of the workpiece, which are hard to predict and to control.

Finite-Element-Simulation is possible, but very time-consuming.

The accuracy of the workpiece depends on a multitude of parameters.

Weld seams

Welding job with many possible sequences FE-model: mesh, constraints and clamping situation

x

yz

Weld

seam

FE-mesh

Clamping

devices

Welding

direction

1 mm

PNd:YAG = 3,0 kW; PHLDL = 3,0 kW; v = 1,0 m/min, Al

Calibration of the heat source model

Simulated

distortions

Source: Schober, Belitzki, iwb



29

Artificial Neural Networks and Evolutionary Algorithms (EA) to Minimize Welding

Distortions

Evolutionary Algorithm: beneficial for calibration of the Heat Source Models

Artificial Neural Network: capable of handling the multiplicity of parameter settings

Evolutionary Algorithm: determines the minimum distortion at the final joint closing the frame

random paramater setting

optimized parameter setting

Training data (from simulations)

Pro

ce

ss

pa

ram

ete

rs

Dis

tort

ion

resu

lts

for

EA

Evolutionary

AlgorthmArtificial Neural Network

Selection

Recombination

Mutation

Reproduction

of process

parameters

minimizes a

fitness function

representing

the distortions

distortion




Agenda

30

5

4

3








31Sources: Bosch Rexroth, Jenke, technikreport 7-8 /15, p. 22

Bosch Rexroth (a manufacturer of drive and control technology) is implementing

Industry 4.0 on the shop floor step by step … small but quick steps

Gain experience in pilot projects (there are more than 100 such projects in the Bosch-

group)

Semi-automatic production line with more than 200 different hydraulic valves

Via an RFID-tag the workpiece authenticates itself at the machines

Bosch contributes to standards in different national and international committees

Bosch Rexroth Group (AG) … is implementing pilot projects

© iwb – Institute for Machine Tools and Industrial Management 32Sources: Thomas Schulz, General Electric, in technikreport 7-8 /15, S. 18 ff.

Industry 4.0 and the Internet of Things are of high significance for General Electric

Data based services for the customer aiming at a more efficient use of General

Electric products (jet engines, trains, power plants, wind energy plants)

Predict-and-Prevent-Model instead of a repair oriented approach

Just like Bosch, GE also contributes to standards in different national and

international committees.

General Electric Company Corporation Definitely Sees High Significance …





Agenda

33

5

4

3







Recommendations and Summary

34

• Implementation of demonstrators / prototype

applications

• Implementation of education and training

centres

• Technology transfer

• Contributions to technical standards

• Less talking / more action

Support for Industry


Recommendations and Summary

Industry 4.0 stands for the vision of a fully

interconnected production system.

Objectives are (among others):

Increased flexibility (lot size 1)

Increased productivity

Reduced time to market

Industry 4.0 is not a job killer, it is a job creator,

because it does improve the competitiveness of

enterprises, which use it wisely.

Industry 4.0 is not a revolution. Everyone still has the

chance to come aboard.

Everything has to be developed and earned. There is

very little that can be purchased off the shelf.

35


7th International Conference on Virtual Machining

Hamilton, Ontario, 7 – 9 May 2018

Michael F. Zaeh, Prof. Dr.-Ing, TU Munich, Germany

(Institute for Machine Tools and Industrial Management)

Michael F. Zaeh, Prof. Dr.-Ing.


Technical University of Munich

37

The Garching Campus of TU Munich

Source: TUM

Some numbers: Founded in 1868, 14 departments, 500 professors, 10 000 staff, 40 000 students


Fields of Research at iwb

38

Factory Planning(Prof. Reinhart)Technology Management, Human Factors, Bionics

Machines and Robots(Prof. Reinhart, Prof. Zaeh)Structural Behaviour, New Applications

Technologies(Prof. Zaeh)Cutting, Joining,

Additive Manufacturing

Institute for Machine Tools and Industrial Management


iwb at Garching near Munich

39

Our laboratory

2 prof., 61 researchers, 17 supporting staff, 6 management team, budget 10 MEuro p.a.


Research Associate

Institute for Machine Tools and

Industrial Management

Faculty of Mechanical Engineering

Technical University Munich

Boltzmannstraße 15

85748 Garching

Tel. +49.89.289.

Fax +49.89.289.15555

www.iwb.tum.de

Michael ZaehProf. Dr.-Ing.

15502

[email protected]

40

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Industry 4.0 in a Nutshell What is really new? · • Internet Banking • Flight and travel...

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