© marc le goc - lsis - dls03 dec 3-4 - tucson1 extensive large scale real time knowledge based...
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© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 1
Extensive Large Scale Real Time Knowledge Based Systems Design: the Sachem Example
Marc LE GOCLSIS, Laboratory of Sciences of Information and SystemMarseille, France
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 2
Content
Sachem and the Blast FurnaceSachem DesignCurrent Works
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 3
Arcelor is the world ‘s first steel producer
• 45 millions tons per year, >100 000 employees, $33 billions of turnover.
Estim
ates
43,5
28,6
20,2 19,3 19,117,7 16,5
1513,3
27,1
Arcelor (Luxembourg)
Posco(South Korea)
NipponSteel
(Japan)
NKK(Japan)
LMN (Ispat
London)
ShanghaiBaosteel(China)
Corus(United
Kingdom)
Thyssen Krupp Steel(Germany)
Riva(Italy)
Kawasaki(Japan)
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 4
• 1 300 MW for6,000 tons of hot metal / day
• ~1200 sensors• Extreme conditions (high
T°, dust, acidity, etc)• No mathematical model of
the dynamic• Long period for learning (5-
10 years)
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 5
Sachem goal:
•Optimize the BF operation in order to save up 1€/ton of hot metal (i.e. 1% of the cost price)
• 1 300 MW for6,000 tons of hot metal / day
• ~1200 sensors• Extreme conditions (high
T°, dust, acidity, etc)• No mathematical model of
the dynamic• Long period for learning (5-
10 years)
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 6
Sachem optimises the BF by reducing the deviation of its parameters
Instrumentationcomputer
~5500 Variables
StateCorrection
Event DB
Data Acquisition
& Model Processing
State Perception& Diagnosis
OperatorCommunication
Monitoring
1,100data/mn
Process DB
Data Base Management
~150 Phenomenon / day~10 Actions / day
~70 Msg / dayAlarms/Action
Justifications
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 7
Sachem represents ~415 000 lines of « C » equivalent code
StateCorrection
10%
Data Acquisition
& Model Processing
20%
State Perception& Diagnosis
33%
OperatorCommunication
20%
Monitoring
7%
Data Base Management
10%
•21 Knowledge Bases
•1060 Object Classes
•1100 First Order Rules
•140 Chronicles
Development:
•~30 engineers from 1991 to 1998
•150 man.year (~30 m€)
Knowledge acquisition & modeling:
•12 Experts, ~6 knowledge engineers
•14 man.year over 3 years
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 8
With 6 Sachem in operation, the Arcelor Group earns ~18,5 m€ per year
Frequency of Incidents
0
5
10
15
20
25
30
Reference Level
Expected level
Without S
achem
With Sachem
Low Hot Metal T°
Thermal LossesBurden Descent
TOTAL
Target Result
Sachem save up ~1,7€ per ton of hot metal
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 9
Extensive Large Scale Real Time Knowledge Based Systems Design: the Sachem Example
Sachem and the Blast Furnace
Sachem DesignCurrent Works
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 10
Sachem is designed a as recursive abstraction process of discrete events
Process State
Signals
Quantization
Signal Events
Discrete trajectoriesInterpretation
Signal Phenomena
Detection
Process Phenomena
Logical Sensors
Sta
te P
erce
ptio
n
Process Behavior
Process BehaviorAnalysis
Process Problems& Causes
Recommend
Recommendedactions & warnings
Process State
Logical Actuators
Dia
gnos
eC
orre
ct
Process Phenomena
Recognition
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 11
Requirement’sdefinition
SoftwareSpecification
TechnicalDesign
Implementation
CommonKads Model Transformation Process, within a spiral development
SachemRequirement
SpecificationModel
DesignModel
DataModel
FunctionModel
BehaviorModel
KnowledgeAnalysis &Modeling
KnowledgeModel
Concept’sModel
Inference’sModel
Task’sModels
SACHEM
25,000 objects:
• 3200 concepts, 2000 relations
• 75 inference structures
• 33 goals, 27 tasks
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 12
Requirement’sdefinition
SoftwareSpecification
TechnicalDesign
Implementation
Sachem Template Knowledge Model for Monitoring and Diagnosing
SachemRequirement
SpecificationModel
DesignModel
DataModel
FunctionModel
BehaviorModel
KnowledgeAnalysis &Modeling
ConceptualGenericSachem
KnowledgeModel
Concept’sModel
Inference’sModel
Task’sModels
Validated in collaboration with the LSIS by simulation (using Petri Nets formalism)
SACHEM
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 13
Sachem Framework for an Adaptative Generic Monitoring Cognitive Agent
Generic SachemMonitoring and
DiagnosingMethod
KernelCompilation
Implemented Sachem Template Knowledge Model
GenericBlast Furnace
Generic ProcessKnowledge
Knowledge BasesConfiguration
…GenericProcess#2
Fo
s#1
Specific ProcessInstrumentation
Structure
FunctionsParameterization
150 man.year
MT
#1
~5 man.year
Fo
s#2
Du
k#4
~1 man.year
Pat#6 … …
~0.5 man.year
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 14
Extensive Large Scale Real Time Knowledge Based Systems Design: the Sachem Example
Sachem and the Blast FurnaceSachem Design
Current Works
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 15
One of the advantages of discrete event representation is compactness
• 50 000 octets of the Sachem Process Data Base are required to produce one octet in the Sachem Event’s Data Base
• One year of blast furnace behavior is ~30,000 events• Event’s Data Base = 4.7Mb Sachem Digital Data base = 235,000 Mb
• 15 years of blast furnace (450,000 events) is only ~70Mb !• To be compared with 15*235,000Mb = 3,525Gb !
Sachem Process Data Base(~5500 variables)
500 < Factor < 1000
Events Log
50 < Factor < 100
CompactnessFactor = ~50 000 Process Data (~1100
variables)
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 16
The « Elp Laboratory » aims at learning from an event flow
Events ExpertKnowledgeEngineer
Signatures ELP Lab SACHEM
A signature show the way a type of event is generated
New Knowledge to improve the perception of the process state
© Marc LE GOC - LSIS - DLS03 Dec 3-4 - Tucson 17
Event’sData base
Signatures
ELP ModelsEditor
ExpertELP Models (DEVS formalism)
Model Recognition(DEVS Simulator)
Event FlowAnalysis
(Markov Theory)
ELP Lab
Sequences ofEvents
A signature show the way an event type is produced by a couple (Process, MCA)
Discrete EventModels