Z umetno inteligenco do večje prožnosti in

Z umetno inteligenco do večje prožnosti in

nižjih stroškov proizvodnje

Prof. dr. Niko Herakovič,

Fakulteta za strojništvo, Univerza v Ljubljani, Laboratorij LASIM

GZS, SRIP ToP

Quelle: Giant bicycles

Bicycles 1980 Bicycles 2017

• Over 63 different bicycles from just one manufacturer,

available … in different frame sizes,

in different colors,

with different forks,

with different gearshifts,

with different handlebars,

with different cranks,

etc.

A huge amount of product

variants must be handled!

Izzivi - Naraščajoče zahteve kupcev in število variant izdelkov

Vir: FESTO

Standard based cylinder DSBC, ISO 15552 Theoretical variance DSBC:

195,360 combinations

plus SA (special applications) and EWK

Ali se ti cilji v I 4.0 kaj spreminjajo?

Nekaj ciljev v podjetjih, ki jih zasledujemo že veliko let …

NE !!!

Povečanje učinkovitosti, razpoložljivosti in

zanesljivosti proizvodnih, logističnih procesov itd.)

Povečanje produktivnosti in konkurenčnosti (OEE, …)

Skrajšanje pretočnih časov in dobavnih rokov

Zmanjšanje zalog in inventarja

Zmanjšanje napak, motenj in izmeta

Individualizacija izdelkov, fleksibilnost, agilnost, …

Zmanjšanje porabe energije, manj ogljičnega odtisa…

Učinkovitost

(proizvodnih)

procesov v

večini

podjetij

DV: 5 to 10%

100% NDV: Potrate!

90 to 95%

Mechanization:

Mechanical production

Industrialization:

Mass production

Automation:

Electric automationCyber-physical systems:

Integrated automation

Technical

inventions

Organizational

inventions

Technical

inventions

Organizational

inventions

1. Industrial

Revolution

2. Industrial

Revolution

3. Industrial

Revolution

4. Industrial

Revolution

Od I3.0 do I4.0| Poudarki posamezne industrijske revolucije

Vir: FESTO

Smart production nodes

Pametna proizvodna vozlišča

Smart robot cell

Pametna robotska

celica

Fleksibilni, agilni in transparentni proizvodni in

logistični sistemi so ključni za dvig

produktivnosti in dodane vrednosti.

Tehnologija DIGITALNIH DVOJČKOV z vgrajenimi

DIGITALNI AGENTI na osnovi UI omogoča

izvajanje samodejnih odločitev, sprotno

programiranje in kreiranje delovnih ciklov robotov

in drugih podsistemov v realnem času brez

programiranja v naprej.

Napredni proizvodni in logistični sistemi in procesi

Pametna tovarna

Pametni Proizvodni Ekosistemi

Vir: Peralta, Soltero, 2020

Proizvodnja prihodnosti (pametna tovarna) – izdelki morajo …

Vir: Zühlke, Smart Factory, 2015

[2001:0db8:85a3:08d3:1319:8a2e:037

0:7344]

…have a unique identity and memory (by birth)

IPV6

… imeti edinstveno identiteto in spomin…have a standardized

network interface

7654321

WiFi

IP

OPC UA

Services

…imeti standardizirane mrežne vmesnike

…offer autonomy…nuditi avtonomijo

…be locatable at all times

…biti lokalizirani vvsakem trenutku

CAD model

Product model

Communication model

Service model

R Resource and Energymodel

…be described by models… biti popisani z modeli

…be treated asabstract objects

… biti obravnavani kot abstraktni objekti

I 4.0 Izzivi avtomatizacije vrednostne verige

Vir: FUJITSU

Svetilniška podjetja

v svetu:

Foxconn Shenzhen, Bosch

Automation, BMW, Tata Steel,

Procter & Gamble, Rold

AI: Srce pogona rasti svetilniških podjetij v svetu

Vir: Jay Lee, Jaskaran Singh, Moslem Azamfar, Industrial Artificial Intelligence

Strojno učenje namesto programiranjaVele-podatki v Pametni tovarni

Vpliv industrijske AI: Od reševanja vidnih problemov, do preprečevanja nevidnih problemov


Arhitekturni model uporabe AI

v industrijskem okolju – analitika podatkov


Prediktivno vzdrževanje CNC stroja z digitalnim dvojčkom

Vir: Jay Lee, Jaskaran Singh, Moslem Azamfar, Shahin Siahpour; Integration of digital twin and deep learning in cyber-physical systems: towards smart Manufacturing, IET Journals, 2021

25 vodilnih držav v in Industrial DigitalTransformation - alphabetical order

Vir: World Economic Forum, A.T. Kearney, 2018

Austria, Belgium, Canada, China, Czech Republic, Denmark, Estonia, Finland, France, Germany, Ireland, Israel, Italy, Japan, Republic of Korea, Malaysia, Netherlands, Poland, Singapore, Slovenia, Spain, Sweden, Switzerland, United Kingdom and United States.

DIGITALNI DVOJČKI in

DIGITALNI AGENTI

Digitalni model proizvodnega procesa

Vloga digitalnega dvojčka pri podpori krmiljenja proizvodnih procesov in operacij v kibernetsko-fizičnih

proizvodnih sistemih

Vir: Elisa Negri et. al.: Field-synchronized Digital Twin framework for production scheduling with uncertainty, Journal of Intelligent Manufacturing, 2021

Ekspertni sistem s simulacijo

v REALNEM času

UI - Algoritem

Digitalni dvojček

Sodobne IT tehnologije

PLC, SCADA, MES, ERP,

PLM

Optimizacija tlorisa proizvodnje, razporeditve

strojev, podsistemov,…

Analiza procesnih časov, razpoložljivosti

realni procesi

Analiza toka material: zaloga, komisioniranje,

transport, logistika

Razvrščanje delavcev (Izmene / osebje)

Proizvodna naročila/zaporedja, proizvodni

plani

Logistični procesi

Nadzor tovarne

Poraba energije

IZBOLJŠAVE UČINKOVITOSTI PROCESOV

Prikaz in optimiziranje z digitalnim dvojčkom

KPI vrednosti in zmogljivost procesa

Statistična analiza procesnih parametrov

Možnost izvajanja KAJ ČE scenarijev in

optimizacija procesov v realnem času

SIMULACIJA, DIGITALNI DVOJČKI in UMETNA INTELIGENCA

Raziskave in razvojIzobraževanje in vaje za

študente

Testno okolje za projektno delo Izobraževanja, treningi in

delavnice za industrijo

Vizija in glavni namen Demo centra Pametna tovarna - LASIM

Source: Roland Berger

„Factory 4.0" – Extremely increased complexity, constantly changing distributed systems, ever shorter working cycles, a demanding and volatile market ...

PROCESS 2

REFERENCE PARAMETERS

SUB – PROCESSES n

PARAMETERS

I/O UNIT

LOCAL AGENT

-MATHEMATICAL MODEL

-ARTIFICIAL INTELLIGENT

HUMAN

Internet, Ethernet, ...


SUB – PROCESS 1

SUB – PROCESS 2

SUB – PROCESS 3

x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT

LOCAL AGENT

-MATHEMATICAL MODEL

-ARTIFICIAL INTELLIGENCE

HUMAN


TRACEABILITYTRACEABILITYTRACEABILITYTRACEABILITY

PROCESS 1 (deep

drawing)


MEASUREMENT SYSTEM

HYDRAULIC PROCESS

n - PROCESSCONTROL PROCESS

x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn PARAMETERS

I/O UNIT

LOCALCLOUD

LOCAL AGENT

-MATHEMATICAL MODEL


LOCAL PRODUCTION PROCESSHUMAN

PRODUCTION LINE 1

PRODUCT/PART 1

PRODUCT/PART 2

PRODUCT/PART n

FIELD DEVICE n

FIELD DEVICE 2

FIELD DEVICE 1

DIGITAL AGENT – LOGISTICS (INTERNAL, EXTERNAL)

DECISIVE DIGITAL AGENT

Inte

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GLOBAL CLOUD


BUSINESS PLANNING

STRATEGY & GOVERNANCE



...

. . .

. . .Internet, Ethernet, ...

PROCESS 2


SUB – PROCESSES n

PARAMETERS

I/O UNIT

LOCAL AGENT

-MATHEMATICAL MODEL

-ARTIFICIAL INTELLIGENT

HUMAN


PROCESS 1

REFERENCE PARAMETERSLOCAL AGENT

-MATHEMATICAL MODEL


HUMAN

PRODUCTION CELL


WAREHOUSE MANUAL WORKPLACE / WORKER. . .

. . ....... ... ...

PARAMETERS PARAMETERS PARAMETERS

PARAMETERS PARAMETERS PARAMETERS

DIGITAL TWIN DIGITAL TWIN DIGITAL TWIN DIGITAL TWIN

DIGITAL TWIN DIGITAL TWIN DIGITAL TWIN

LOCALCLOUD 6

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DIGITAL TWIN (Production line 1)

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LOCALCLOUD 7

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LOCALCLOUD 8

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LOCALCLOUD 9

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DIGITAL TWIN (Production cell) DIGITAL TWIN (Warehouse) DIGITAL TWIN (Manual workplace). . .

DIGITAL TWIN - logistics

Internet, Ethernet, ...Internet, Ethernet, ...

Performance

Intiatives & Programs

Budget

Balanced Scorecard

Strategy

ReportingFunding

Update the strategy

Test the hypothesis

INPUT (Resources)

OUTPUT (Results)

Management Control Loop

Strategic Learning Loop

85% of management teams spend less than one hour per

month on strategy issues

92% of organizations do not report on lead indicators

LOCALCLOUD 2

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LOCALCLOUD 3

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LOCALCLOUD 4

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LOCALCLOUD 5

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FACTORY OF INDUSTRY 4.0

TRACEABILITY TRACEABILITY TRACEABILITY


PROCESS 2


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I/O UNIT

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-MATHEMATICAL MODEL


HUMAN



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SUB – PROCESSES n

PARAMETERS

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x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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-MATHEMATICAL MODEL


HUMAN


DIGITAL TWIN

LOCALCLOUD 10

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x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

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...

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PROCESS 1


-MATHEMATICAL MODEL


HUMAN


DIGITAL TWIN

LOCALCLOUD 11

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x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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PRODUCT/PART n

PROCESS 1


-MATHEMATICAL MODEL


HUMAN


...

PARAMETERS

DIGITAL TWIN

DIGITAL TWIN

LOCALCLOUD 12

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TRACEABILITY

SUB – PROCESSES n

PARAMETERS

SUB – PROCESS 1

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SUB – PROCESS 3

x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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PROCESS 1


-MATHEMATICAL MODEL


HUMAN


DIGITAL TWIN

LOCALCLOUD 13

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x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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PROCESS 1


-MATHEMATICAL MODEL


HUMAN


DIGITAL TWIN

LOCALCLOUD 14

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x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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PRODUCT/PART n

PROCESS 1


-MATHEMATICAL MODEL


HUMAN


...

PARAMETERS

DIGITAL TWIN

DIGITAL TWIN

LOCALCLOUD 15

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TRACEABILITY

SUB – PROCESSES n

PARAMETERS

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x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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PROCESS 1


-MATHEMATICAL MODEL


HUMAN


DIGITAL TWIN

LOCALCLOUD 16

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PARAMETERS

SUB – PROCESS 1

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x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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PROCESS 1


-MATHEMATICAL MODEL


HUMAN


DIGITAL TWIN

LOCALCLOUD n

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SUB – PROCESSES n

PARAMETERS

SUB – PROCESS 1

SUB – PROCESS 2

SUB – PROCESS 3

x1, x2, ... ,xn y1, y2, ... ,yn z1, z2, ..., zn

I/O UNIT


...

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LOCALCLOUD 1

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PC

MOBILE PHONE

TABLET COMPUTER

LOCAL VISUALISATION OF PRODUCTION LINE 1

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VISUALISATION OF LOCAL PRODUCTION

PROCESS

PC

MOBILE PHONE

TABLET COMPUTER


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PC

MOBILE PHONE

TABLET COMPUTER


PROCESS

PC

MOBILE PHONE

TABLET COMPUTER


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PC

MOBILE PHONE

TABLET COMPUTER


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PC

MOBILE PHONE

TABLET COMPUTER

LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESS LOCAL PRODUCTION PROCESSLOCAL PRODUCTION PROCESSLOCAL PRODUCTION PROCESS

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LOCAL VISUALISATION OF PRODUCTION CELL

CONT

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LOCAL VISUALISATION OF WAREHOUSE

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LOCAL VISUALISATION OF MANUAL WORKPLACE

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VISUALISATION OF PRODUCTION HALL

PRODUCTION HALLIn

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Referenčni Arhitekturni Model Industrije 4.0

RAMI 4.0

Arhitekturni model pametne tovarne LASFA(Lasim Smart Factory)

prezi-windows.exe

prezi-windows.exe

D.A.I.

D.A.O.

D.A.M.

D.A.A.

D.A.J.

D.A.D.

G.D.A.

Vgradnja digitalnih agentov (UI) za sprotno optimizacijo proizvodnih in logističnih procesov

Digitalni dvojček (CPS) in digitalni agenti (UI)

DIGITAL TWIN

D.A.I.

D.A.O.

D.A.M.

D.A.A.

D.A.J.

D.A.D.

G.D.A.

R&D reference olaboratorija LASIM

https://dih-ditmaps.si/

Hvala za vašo pozornost!

https://dih-ditmaps.si/

Kontakt: Prof. dr. Niko HerakovičE-mail: [email protected].: +386 1 4771 726

Laboratorij LASIM, Fakulteta za strojništvo, Univerza v LjubljaniAškerčeva 6, 1000 Ljubljana, Slovenija

https://web.fs.uni-lj.si/lasim/

mailto:[email protected]

Z umetno inteligenco do večje prožnosti in

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Transcript of Z umetno inteligenco do večje prožnosti in