Base of The Fourth Industrial Revolution Modularization · PDF file ·...

SV.1

PD Dr.-Ing. habil. Jörg Wollnack 18.12.2015

Base of The Fourth Industrial Revolution

Modularization and the Things

Adaptive Production Technology

Example Applications

SV.2


The Fourth Industrial Revolution

Data relationships needs Models

The Internet of Things

Big Data, Smart …

IPV4 232 10 9 Addresses

IPV6 2128 1038 Addresses

Lot Size One

Individual Production

Tolerance and Unique

The Measurement of the World is not new Humboldt and Gauss

What’s it?

SV.3


Software

Hardware

Intel Button PC (20nm Chip Design)

World Wide Web

W-LAN

Model Kit

The Internet of Things

Multidimensional

Input Output Signals create Big Data

1000 cores

and more

SV.4


Information, Signal and Model

MaxN 2

Noise

N log 1 [bit/s]S

S

frequency

Information

signalvalue

timenoise

f

t

S

Max

Min

p

2

( )N d [bit]

log ( )

S

S

p ss

p s

Signal Entropy

Entropy per Seconds

Channel Capacity

MaxMax 2

Noise

C 2 log 1 [bit]S

fS

Deterministic and constant multidimensional signals or

models do not contain Information. We must identify these

only once.

Only random multidimensional signals or models contain

information. Signals must measured online and models must

be identified online.

Average values and statistical spreads or the covariance

matrixes are only first order approximations. These lead in

practice to relatively big errors between model and reality.

SV.5


The multi-dimensional Fourier transformation

of probability density function is equal to the

multi-dimensional empirical statistical central

moments. These can be measured!

We need Big Data, Advanced Mathematics

and at the End

Software for this.

SV.6


The humans must design the

Software. The computer is not

creative and not intelligent in

the sense of humans.

The software is not intelligent.

The software designer is it.

The Rule of the Humans

We must design a deterministic

and stochastic static and

dynamical multi dimensional

process and product model in

the software.

SV.7


Modularization

and

the Things

SV.8


FANUC

ABB

FANUC

Modularization and Things I

Drives,

Actuators

and Robots

External Sensors 6D Pose and

6D Force

Controls and

Feedback

Controls Beckhoff Siemens

KUKA FANUC

ABB

KUKA

Leica Nikon

Aikon

Linear

Drive

Rotational

Drive

Parallel

Kinematics

Serial

Kinematics

Hybrid-

Kinematics

Indoor-GPS Laser Measurement Technique

Video Metric Measurement

SV.9


Gripper

Tool Change

Spindle

6D-Calibration

6D-Gripper and

Tool Calibration

Auxiliaries

3D/6D Marker external or/and

product integrated LED-

Points Edge

Elements Sphere

rR

Triple Mirrors Retro Reflective Marker

(wavelength selective)

Tool Change Systems Gripper

Milling

Spindle

Calibration Bodies and -auxiliary

Modularization and Things II

SV.10


Adaptive

Production Technology

SV.11


Adaptive Production Technology

Position Error

Components

(5 – 10 mm)

Position Error

Linear Axis

(5 – 20 mm at the

Process)

Position Error

Robot

(1 – 5 mm)

Position Error

Process to TCP

(0,5 – 1 mm)

Process Force Position

Influence

(0,5 – 1 mm)

Accuracy

Requirements

(0,1mm Range

from 10 to 20m

5µm/m)

SV.12


Example Applications

SV.13


Adaptive Production Technologies

SV.14


Automated measurement, placement,

calibration of process,

part and machine models

• Adjustment, machining and assembly of CFRP large

component after technologically weighted best

fit criteria

• Tolerance management by high precision calibration,

adaptive path planning as well as actuator controlled

shape and position correction

• Optimized hierarchical fully automated calibration of

control models of serial and parallel machines as

well as robot systems

• Sensor guided adaptive CFRP production

technologies

Laser-Tracker

3D-Videometrie

kooperierende Multi-Robotersysteme

steiferBauteilbeschlag

elastischerBauteilbeschlag

3D-Messmarke

Montagebauteil

Master-Roboter

Slave-Roboter

Tool-Grabber-Sensor

STCP

SM

SG

SR

Walking-Rivet-Robot

Roboter

CAS CAD CAM Data Link I

CA := Computer aided, S := “sensoring”, D := Design, M := manufacturing

The Fourth Industrial

Revolution

We are already

started!!!!

SV.15


Siemens

Control Level

Leading Level

Cell Level

Field

Level

Actuator

Sensor

Level

µs to ms

ms to s

seconds to minutes

minutes to days/months

CAS CAD CAM Data Link II

Shannon Sampling Theorem (high dynamic result in high sampling rates;

no lost information)

The

Internet

of

Things

High Level

Language

C++ or C#

S B2 , 5 to 10f q f q

f := frequency

B := band width

S := sampling

Hard Real

Time

SV.16


Adaption and 0.5 to 1.5 Bill. €

costs reduction potentials (Robot production cells on linear axes versus construction of special purpose

machines require flexible problem adapted optimal linear axis and robot calibrations

or/and sensor guided robots; Otherwise special machine necessary)

Teach costs per Product 1,000€ to 30,000€ (dependent on the number of teach poses;

various processes till now not possible)

Teach costs per Robot 10,000€ to 300,000€ (10 Products per Robot)

Robot change in production line 100,000€ to 400,000€ (Reapplication of teaching Production holdup)

Amortization Potential

SV.17


Rough Inter-polation

Inverse kin.Transform

Look-UpTable

Fine Inter-polation

PositionRegulator

MachineCoordinates

IdentifiedMachine/Robot

Parameter

Time Sequence

{ }tk

xG( )tk

xF( )tm

pRI

pRI pEI

pRI

xTCP

A( )t

Motion Model geomtric Parameter

AxisSensor (x)

Velocityand Acceleration

Definitions

pTCP

A( )t vTCP

A aTCP

A

< 10ms

Time Sequence

{ }tm

< 1ms

PowerAmplifier

Sensor(x,x,x)

Comp. AxisResidual Moments

x( )tm

x( )tm

x( )tm

FrictionCompensation

x( )tm

+ -

Interpreter

ServoControl

ElasticityModel +

-

Target Pose

pTCP

AS( )t

xS( )tm

xS( )tm

xS( )tm

Fast iterative-inverse

under consideration of

parallelism and orthogonality

errors of the axes as well as

drive elasticity. (500 high-speed compared with

classic iterative approaches Makes

10 ms possible for precision

calibration applications and realize

real time abilities !!!!)

Hierarchical iterative model

calbration orientated at the

numeric rank defects and the

sensitivity of the control model

parameters (Realize fully automatic high speed

precision calibration)

6D position invariant modeling

of the elasticity behavior

(Realize a real time compensation

of process force induced 6D

position variant positioning errors.)

Analytical identification of 6 D

transform measuring to TCP

frame (Identification 6 D-measuring

characteristics, Identification 6 D tool

correction,

Identification of cooperating multi-

robot systems, Precision model

calibration etc.)

Automation and System Integration

These Principles are General Applicable

Modeling Structure and Parameter Identification

Inverse Models / Controller Loops

Information Gain by Measuring

Integration of the procedures

to the cell level

or under

real time requirements into the field level

SV.18


F-Aromon

Adaptive milling

processing

Adaptive component

and section assembly

Adaptive component shape and position correction

CFK AFMO FFM

Examples

ProsihP FFM

SV.19


Component Shape and Positional Correction

• Flexibly adjustable contour

(for several aircraft types usable)

• Economical vacuum grab systems

• 6 D force and moment controlled process

• Wrinkling could reduced

• Temperature and range of the tide compensation

• Adaption in the shape and positional correction

• Economical foundations

• Shape and position precision converges towards the machines repeatability to 2 - 4

iterations in the area of 50 to 100 µm (for the hole fuselage)

SV.20


Hand Eye Calibration

Movement

Measure

Iterative Model Calibration

SV.21


CAS CAD CAM Link

SV.22


Joint-Controll

Network-Card

Joint-Regulator

Grob-Inter-polation{ }it

{ }kt

Bewegungs-variante G

Maschinenkoordinaten

Geschwindigkeits-und Beschleunigungs-

vorgaben

Zeitfolge

Zeitfolge

AnalytischeInverse

Fein-Inter-polation

Lage-regler

Trans-formation

TCP

A ( )itp

( )itx

F ( )ktx

I ( )tx

Steuerrechner

I/O-DA

Sensor(x,x,x)

Power-Amplifier

ExternalSensor

Realtime Gigabit Ethernet

EEWEEW

Software

Werkzeugmaschine

Maschinen-steuerung

T-Mac

Wasser-schneid-

ToolLeica-Laser-

Tracker

Fräs-Tool

T-Scan

T-Probe

6D Pose Measurement “On the Fly”

• Reduction of unproductive

measuring and auxiliary

progress times by 80%

• Standardized interfaces

• Modular hardware and

software architecture

• Adaptive flexible production

and assembly cells

• Adaptive path control

• 0.5 to 1 Bill. € per year

SV.23


Calibrated Model

Non calibrated

Model

/ 100 µm

/ 1 mm

RMS x / m y / m

x / m y / m

Model Based Precision Increase

Machine

Application

C, C++, C#

Programmers Interface

ModelingSensor Vision

Motion & I/O - Interface

MotionPlanning

I / O

BlumeBlume

Sensors

OfflineProgramming

and Simulation

Sensor-Int.

I/O

Motion

Robots

OperatingSystem

KernelMode

User Mode(protected)

Hardware Interface Layer

Hardware

Filesystem

OtherDeviceDriver

NetworkDrivers

GraphicsDrivers

GraphicsSubsystem

I/O Manager

Real Time

OO Code Classes API Vision

• Structured model based instead of

unstructured (look up table) volume metric

6 D position error compensation

• Application for assembly and production

facilities, large volume machine tool as well

as industrial robots

• Significant reduction of the measuring

time by 95%

• Automatic causal detection of wearout,

defects etc..

• Accuracy gain (factor 5 to 10)

• Recorded Quality

• 0.5 to 1.0 Bill. € per year

Base of The Fourth Industrial Revolution Modularization · PDF file ·...

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