1

Intelligent Manufacturing roadmap

“Towards the process industry lean factory of the 21st century”

Document prepared by the Intelligent Manufacturing WG (WG1-Profit)

L. Chefneux (ArcelorMittal, chairman)

Members : S. Fera (Riva), N. Goldenberg (Siemens), W. Moonen (Corus), A. Mouchette (ArcelorMittal), H. Peters (BFI), C. Pietrosanti (CSM), L. Sancho (ArcelorMittal), G. Tourscher (ArcelorMittal)

September 3rd 2009

2

Challenges for the process industry All industries have to control their production in order to serve the

customer with the best product , just in time and at minimal cost , in a sustainable way

Sustainable and Lean manufacturing are the objectives to be achieved

This concept mainly developed in discrete manufacturing has to be extended to process industries ( continuous or semi-continuous )

In particular the materials producing industries (steel , aluminum , other non ferrous, ferroalloys,

glass, paper , cement , chemical) are facing very important challenges : - CO2 emissions constraints - energy cost and scarcity- raw material cost and scarcity- logistic constraints - ecological footprint - sustainability

Intelligent Manufacturing gives the integration tool permitting the global control of the whole production chain supporting the Lean manufacturing deployment

3

Definition of IM for material process industries

Intelligent manufacturing is the progressive building of

an integrated control of manufacturing chains including all technological aspects ( utilization of sensors , process control loops , IT systems , production scheduling …)

with

the addition of intelligence provided by modelling , advanced control including cognitive automation concepts, diagnostic and advanced maintenance tools, optimization and simulation, expert knowledge, artificial intelligence…, in good coherence and interaction with human intelligence

TECHNICAL CONTENT / SCOPE

4

Intelligent Manufacturing

CUSTOMERS

Data processingInd. Information Syst.

Supervision, DB Data Mining, KPI.

ModellingPhysics

Statistics, NNMixed

Products Quality & sustainability•Quality Control

•Prediction, correction

Production Chain & global company • Simulation• Costs, route & flow Optimization• Operation Research

Production Lines• Advanced maintenance • Automatic control• Diagnostic

Evolution of

present facilities

Eng

inee

ring

Intel

ligen

tMachines

LineProcess

Suppliers LineProcess

LineProcess

Production Chain

Measurements – DataInstrumentation, SensorsValidation, Reconciliation

5

Defining a criterionBased on the concept of integration of different “bricks”,

the 10 generic topics

Sustainable & Lean manufacturing

Real time control

Product driven

Just in time

Cost driven

Use of sensors ( 1)

Use of Data processing

(2)

Advanced maintenance

(7)

Product quality control

(5)

Advanced control(6)

Diagnostic ( 3)

Supply and Productionchain management ( 8 )

Modeling, Simulation& Optimization ( 4)

Knowledge use ( 9)

Integration of processes (10)

Sustainability driven

6

Labelling of an IM project A project could be labelled IM if it concerns at least THREE generic topics (two if

CLEARLY relevant to factory wide aspects) with a significant impact, and dealing with the global control of minimum one big process step (e.g. BF, BOF, CC, HSM, HDG…)*

*Each project asking for the label will pledge to contribute to the IM Roadmap communicating the needed information

PROJECT 1

PROJECT 2

PROJECT 3

Project title and reference

Ad

va

nc

ed

co

ntro

l

Us

e o

f se

ns

ors

dia

gn

os

tic

Mo

de

lling

/sim

ula

tion

&

op

timiza

tion

Kn

ow

led

ge

us

e

Inte

gra

tion

of p

roc

es

se

s

Ad

va

nc

ed

Ma

inte

na

nc

e

Su

pp

ly &

Pro

du

ctio

n

ch

ain

ma

na

ge

me

nt

Pro

du

ct q

uality

co

ntro

l

Us

e o

f da

ta p

roc

es

sin

g

7

Important notice : The main difficulty to implement the factory of the future ! • the ambition must be shared and supported by the whole company. It will require huge investments and to integrate all the functions in the company : technical, financial, IT, quality, maintenance, logistics, purchasing, human resources, as well as R&D

• R&D is a modest player but indispensable. It has to show the way and to be the link between all the functions. A lot of innovations will come from these and from outside through external suppliers and consultants.

• All will be largely depending on the progress in the critical technologies linked with the knowledge driven society : ICT, sensors, AI, KM, micro-technologies

• We will focus here after on the R&D activities supporting this huge ambition !

8

ROADMAP

A continuous progress with overlaps

| | | | | 2008 2010 2015 2020 2025

critical technologies for a knowledge driven society : ICT, sensors, AI…

whole factory wide supervised control

supervised control of factory parts

optimization of process groups

single process modelling and optimization

≈

≈

≈

Short term

Medium term

Long term

≈

≈≈

9

• Short term (2009-2014)

– Projects respecting our labelling criteria and dealing with • Modelling and optimization of single processes• Global control of a consistent sub-part of the production chain • Demonstration of cascaded monitoring and control through some, at

least two coupled production chain links on some specific topics (product quality , energy saving …)

filling as far possible the identified deficiencies pinpointed by examining the recent RFCS labeled projects, as :

• data validation • cost and energy modelling • production scheduling • advanced maintenance• supply chain management

All existing possibilities have to be used to support the efforts, RFCS for steel specific projects, FP for generic ones, with process industries or discrete manufacturing ones, without neglecting the national and regional levels !

10

• Medium term (2015-2019)

– Global control of aggregated sub-parts ,

– Deployment of cascaded monitoring concepts and tools including the supply chain management and customer delivery

IRON and STEEL PLANT Cold,

coating & finishing PLANT HOT

ROLLING

RawMaterial

supplyingCustomer

11

• Keep in Europe an important production capacity, creating added value and wealth

• Reference for our equipment suppliers

• Preserve employment, although contributing to decrease the workforce in the industry

• Socio-cultural impacts linked to the implementation of the knowledge driven society : development and sharing of know-how, change of management practices , HR aspects, education and long-life learning…

SOCIO-ECONOMIC ASPECTS

STAKEHOLDERS• Steel industries

• Suppliers (heavy equipment, IT, high-tech SMEs) and sub-contractors• Research centres, universities (steel, sensors,

automation, IT, KM, human aspects)

• Innovative SME

• Other continuous process industries

• Discrete manufacturing industries

12

To clarify the concept, a success story as didactic example :

ASIS

Automatic Surface Inspection System

13

Application of ASIS some years ago

ASIS: Automatic Surface Inspection Systems

• ASIS of different plants are running independently

• ASIS results are only locally stored and no connection to process data exist

• Very often ASIS are used as “intelligent video recorder”

14

Typical situation today

15

Identified problems

• ASIS are not „measurement“ devices, because the „accuracy“ (reliability) can not be guaranteed

• Results of ASIS from different suppliers are not directly comparable

• Usage of ASIS data is not systematic and not integrated in on-line quality control loops

• No general solutions for typical usage of ASIS data exist, like automatic coil allocation, automatic root cause analysis, etc.

16

Research project starting in July 2009

17

Improvements after successful project completion

• Continuous monitoring of all ASIS components

• Monitoring system gives hints for maintenance actions or adaptations of ASIS parameters

• ASIS data are more reliable and can be used for further purposes

• Task related “surface KPI’s” for one process and the complete process chain are calculated automatically

• Based on the surface KPI’s a systematic supervision of product quality and process performance is realised

• The basis for future on-line quality control of surface quality is ready