Optimize System Design - Hitchinssystems.hitchins.net/.../incose-tutorial/optimize.pdfOptimize...

30/04/16 dkh©2004 1

Optimize System Design

Derek Hitchins

30/04/16 dkh©2004 2

Why Optimizing is Important •  Optimization results in the “best” solution to the

problem, where best may be: –  Best value for money –  Lowest risk of Blue casualties –  Most cost effective –  Maximum ROCE… –  …and many more

•  Generally, optimization is about compromise –  E.g most cost-effective ≠ most effective

•  Most effective may be unaffordable

–  Apollo compromise was about mass, volume, capability and risk between the various parts

30/04/16 dkh©2004 3

Effectiveness •  Measuring the effectiveness of LF2020 – it

has slipped a decade after looking at the technology– will be more difficult, but vital

•  What is meant by effectiveness? – Cost effectiveness, cost exchange ratio, casualty

exchange ratio, ROCE? Or all of these? •  In practice, it seems that effectiveness—the

degree of effect that one system has on another—is not fixed –  It varies throughout an engagement, for

instance…

30/04/16 dkh©2004 4

Introducing a Reference Model •  At this point we will use a Reference Model

– Encourages completeness of solution •  Each element in Reference Model should find

correspondence in designed solution

– A good reference model will make measurement of the system solution easier

– With simple measurement comes the facility to optimize the design, i.e. maximize/minimize the appropriate measure

– We will use the Generic Reference Model •  See www.hitchins.net/systemstop.html

– This should help us understand effectiveness, too

30/04/16 dkh©2004 6

Generic Reference Model •  GRM describes “internals” of any

system –  essential features, capabilities – must exist for a system to be:—

•  complete, •  functional, •  and—if appropriate— •  sentient

•  GRM does not describe:— –  conception, creation, becoming viable,

decay, decommissioning, etc. –  any external features

30/04/16 dkh©2004 7

BehaviourManagement• Cognition

• Belief System• Selection

• Intent

Funct ionManagement

• Mission• Viability• Resources

Fo rmManagement• Structure• Potential• Influence

Being

DoingThinking

Stimulus

System

Generic Reference Model Level A

30/04/16 dkh©2004 8

Inseparability of GRM Aspects •  Possible to view Being, Doing and Thinking

elements of GRM as independent •  Useful as a check-list to see if a system

description has missing elements, but… •  …falls well short of full potential •  Different parts of Model identify different

facets of same system, –  e.g. Thinking affects the manner of Doing; –  Doing depends on Being; –  Being enables Thinking (cogito ergo sum!)

30/04/16 dkh©2004 9

Generic Reference (Function)Model

•  “The Management Set”

30/04/16 dkh©2004 10

Function Model—Laundry List View

Mission Viability

Resources

InformationObjectives

Strategy & Plans

Execution Cooperation

Acquisition Storage

Distribution Conversion

Disposal

Synergy Survival

EvolutionHomeostasis

Maintenance

The Management Set

Collect information

Set/resetobjectives

Strategize& plan

Executeplan

Co-operatewith others

(if necessary)

Operationalenvironment

➤  N.B. work is done in processing information into a plan—energy required to “drive” loop

➤  Internal “push/pull force” maintains loop dynamics

Mission Management

Resourceenvironment

Acquireresources

Storeresources

Distributeresources Convert

and utilizeresources

Discard excess/waste

➤  N.B. Resource management absorbs resources

➤  Storage essential to meet continual internal demand

➤  Internal “push/pull force” maintains loop dynamics

Resource Management

•  Self-sustaining set •  Homeostasis maintains

internal environment for all other internals

•  Synergy co-ordinates all internal parts

•  Maintenance detects, locates, replaces, disposes

•  Survival protects from externals

•  Evolution adapts, improves…

•  Together = Viable System •  c.f. neonate

Viability Management

SurvivalEvolution

Homeostasis

Synergy

Maintenance

Dynamic GR(Function)M •  3 elements seen in

respective “environments”

•  Viability provides platform for Mission Management

•  Resources provide energy & materials for Viability and (internal) operations

•  Threats to Mission Management, Resource Management

•  Change challenges Homeostasis (resist) and Evolution (adapt)

Threat

Survival Evolution

Homeostasis

Synergy

Maintenance

Resourceenvironment


Acquisition

Storage

Distribution Conversion

Disposal

Information

Objectives

Strategy& Plans Execution

Co-operation

Threat Change

30/04/16 dkh©2004 15

Generic Reference (Form) Model

30/04/16 dkh©2004 16

Generic Reference (Form) Model

Boundary Subsystems Connections Relationships Configurations

Structure

PowerCapacity

RedundancyDynamic Range

Potential

Cohesion

DispersionEnvironment

Influence

30/04/16 dkh©2004 18

Background to the Behaviour Model •  Behaviour Model proposes how Behaviour

might be selected generically— –  does not identify which behaviour results from a

given stimulus

•  Of three first-level Models, Behaviour most complex, subtle. –  based on a variety of psychological models –  proposes way in which both instinctive and

sentient entities respond to stimulus –  appropriate for individuals and groups –  recognizes essential nature-nurture conflict –  establishes Belief as central to behaviour

Response�Intent

GRM—Behaviour Management

Cognition

Tacitknowledge

Worldmodels

Stimulus Excitation

Nurture

•  Collective Unconscious

•  Instinct•  Archetypes

•  Libido•  Aggression•  Energy

•  Character•  Emotion

•  Achievement•  Conformance

•  Beliefs•  Rôles•  Stereotypes•  Categories•  Values•  Ethics•  Morals•  Ideologies•  TrainingExperience

BeliefSystem

Environment

Motivation

Behavioural ArchetypesBehavioural Archetypes

Interpretation

Activation

Constraint

Selection

Evolution

Nature

30/04/16 dkh©2004 20

System N2 Chart—and Emergence

…where A and B are any two entities on

leading diagonal

A

B

Decisions, orders &

instructions

Interaction-outflow

Emergenceboundary & interaction

Emergence-endurance

Evidence-stable internal

environment

Emergence-evolution

Emergence-survivability

Evidence of internal order

Outflow- waste, excess

EmergencePerformance & Outflow

•Risk • opportunity

•priorityInforma

-tion

Objectives Purpose

Strategy and Plans Method

Execution

Potential partners

contribution

Partners contribution

(Sibling) Co-operation

ConstraintsShortfalls Constraints

Supply ActivationEndurance

Constraints

Co-ordinationCo-operation




PriorityDirection

PriorityDirection Reflex

Energy efficiency

Inabilities


Entry Exit

Empower-ment

ConfidenceCapability

Risk Threat

DriveOptions

ConfidenceDrive

Drive Drive

OptionsConfidence

Drive

Future needs

Demand

Resourceacquisition

Storage Discontinuous supply

Replenish-ment status


Distribu-tion Localization


Conver-sion

Fresh capacity Disposal

• Residue• Product• Waste

Resource status





Demand

Demand

Residue of faulty parts


Entry

Empower-ment

Channels

Empower-ment

Exit

Threat

Drive DriveDrive Drive

Capabil-ity

Drive

Sub-version

Utilization

Destructive variety

Internal energy source

Location

AccommodationAdaptationAdvance



RegulationControl

RegulationControl

RegulationControl

Upkeep Upkeep Upkeep


Resist-ance

Neutraliz-ation

Distribu-tion

Neutraliz-ation

Neutraliz-ation

Disper-sion

(Internal) Environ

-mentMedia-tion

PowerDrive

Endur-ance Capacity

Neutraliz-ation

Replica-tion

Redund-ancy

Threat

Direction

Self defence

Reserves Status

Demand

Short-term continuance Demand

Replace-ment

Co-ordinationCo-operationSynergy Co-ordination

Co-operation

Survival OpportunityOpportunity

Long-term continuance Evolution



Short-term continuance

Homeo-stasis

Upkeep UpkeepUpkeep Upkeep Mainte-nance



Stealth, damage tolerance

Feedback

Damage toleranceFeedback

Feedback

Feedback

Damage tolerance

Enable-ment

Threat

Feedback

Drive DriveDrive StatusDrive

Reconfigur-ability

Reconfigur-ability

Drive

Commit-ment

Conform-ability

Construct-ive variety








Upkeep UpkeepUpkeep Upkeep

RegulationControl


Exit & entry Enclosure Protection?

Boundary Enclosure Protection?

Sub-systems

Defini-tion

Inter-flows

Connec-tions

Context Relation-ships

Aggre-gation

Enabl-ment

Contrac-tion

Enabl-ment Cohesion

Structure

Structure

Structure

Contain-ment

Disaggre-gation

Degrad-ation

Expan-sion

Degrad-ation

Operating conditions

Operating conditionsCharacter Context

Drive Drive Drive

Reconfigur-ability

Resili-ence

Resili-ence

Drive

Media-tion

Inflow Inflow


Enclosure Protection?

PerceivedSituation

EnergySubstance

Inflow

Resili-ence


Identifi-cation

Interpre-tation

Instinct Instinct

World Model

Cogni-tion

Resili-ence

Environments & entities

BeliefSystem

Exper-ience

Resili-ence

Resili-ence

Context

ContextStimulus interpret

-ationInstinctSpeed

Viewpoint,confidence

View points

Response expectations

Nature Archetypal behaviours

Behaviour Selection

Activa-tion

Behavioural Constraint

Motiva-tion

Excita-tion

Energy level

Confidence, morale

Choice of behaviour

Drive energy

Limits to Excitation

Achievement,conformance

drives

Loosening

Loosening

Media-tion

Media-tion

Media-tion

Tightening

Loosening

Media-tion

Loosening

Stimulus





Inheritance-patt-erns of thought &

behaviour








Stimulus

Stimulus

Stimulus

Stimulus

Stimulus

Stimulus

Stimulus

Stimulus

Stimulus

Culture

Limits to behaviour intensity

Achievement,conformance

drives

Limits to behaviour

choice

• Updates• Continual Belief test

Updates

CuesModels

Updates

Updates

Superimposedviewpoints

Tacit Knowledge

Updates

Low-level knowledge

Reflex

Diversebeliefs

Shared beliefs

Choice of behaviour

Choice of behaviour

Choice of behaviour

Choice of behaviour

Response Intent

Response Intent

Filters on acceptability

Viewpoint

Filters on acceptability

Context, interpret-ations

Choice of behaviour

EnvironmentEnvironment"gives to"

Choice of behaviour

Choice of behaviour

Choice of behaviour

Red—GR(Function) ModelBlack—GR(Form) ModelBlue—GR(Behaviour) Model

Generic Reference Model – Level 0

30/04/16 dkh©2004 22

Effectiveness (2)

•  Blue effectiveness can only be sensibly measured when Blue is interacting , e.g. with Red, in some Operational Environment

Operational

Environment

30/04/16 dkh©2004 23

Effectiveness (3)-Adding Impact of Logistics and Procurement on Operations

Blue effectiveness, endurance, etc., depend on its procurement, supporting

and enabling systems

30/04/16 dkh©2004 24

A Balanced Viewpoint

Form

Behaviour

MissionManagement

ResourceManagement

ViabilityManagement

Environment

LogisticsSystem

ProcurementSystem

DefenceSuppliers

Form Behaviour

MissionManagement

ResourceManagement

ViabilityManagement

LogisticsSystem

ProcurementSystem

DefenceSuppliers

Maintenance

Maintenance

30/04/16 dkh©2004 25

StimulusBehaviour

Management

Behavioural Influence

Structure Influence Potential

CognitionBehaviourselection Stimulation

Collectinformation

Set/resetobjectives Execute

Co-operatewith othersStrategize

& PlanMissionManagement

MissionManagement

BehaviourBehaviour

Form Form

ResourcemanagementResource

management

Acquire

Store

Distribute

Convert


BeliefSystem NatureNurture

Maintenance

Survival

Evolution

Homeostasis

Synergy

ViabilityManagement

ViabilityManagement

GRM in Layers

30/04/16 dkh©2004 26

Strategize & Plan

Worldmodels

Stimulus

BehaviourManagement

Behavioural Influence

Structure

Systems

Influence Potential

Systems Systems

Tacitknowledge

Cognition

StimulusStimulus

Behaviourselection Stimulation

Nature

Constraint

Belief system Training

Ethics &morals

Doctrine

Interpre-tation

Motivation

Collectinformation

Set/resetobjectives

Co-operatewith others

Experience

MissionManagement

MissionManagement

BehaviourBehaviour

Form Form

Stimulus

Maintenance

Survival

Evolution

Homeostasis

Synergy

ViabilityManagement

ViabilityManagementResource

managementResource

management

Acquire

Store

Distribute

Convert


Execute

GRM as Virtual Machine

30/04/16 dkh©2004 27

Instantiated GRM

Mobile Land Force Internal Structures

30/04/16 dkh©2004 28

Synergy

Worldmodels

Formationcontrol

Sensor systems

POL, weapon, spares reserves

Communicationsystems

Weapon systems

Tacitknowledge

CognitionNature


Ethics andmorals

DoctrineMotivation

Experience

MissionManagement

Missionmanagement

BehaviourBehavior

Form Form

ViabilityManagement

Viabilitymanagement


management

Acquire

Store

Distribute

Convert


Homeostasis

Maintenance

Evolution

Constraint

Stimulation

Resourceenvironment


Behavioral archetypes

Transportsystems AcquireAcquire

Synergy = cooperation and coordination between parts to produce desired external effects

Survival = avodiance of detection + self-defence + damage tolerance

Maintenance = detection, location, excision, replacement, and disposal of defective parts

Homeostasis = maintenance of internal environment appropriate to effective subsystems operations

Evolution = accommodation, adaptation, advance

R.A.S.P.

Decision making

Assess situation

Identify threats and

opportunitiesInitiate action

Decisionmode

Generate optionsin sequence

Simulatementally

Y

N

Review allconstraints

Select preferred

option

Recognition-primed decisions

Naive decisions

Monitor

ExecuteInitiate action

Behaviorselection

Generateall options

Survival

Battledamagedisplays

Resourcesdisplays

Formationdisplays

30/04/16 dkh©2004 29

Filling in the Numbers •  Note that all separate land vehicles, UAVs,

FACs, etc., treated as one system – Valid—if we achieve organismic design

•  However, different design options would introduce different values for many of the parameters. F’rinstance – Battle damage might be greater with fewer, larger,

concentrated vehicles. However… – Battle damage repair might take much longer with

more, widely dispersed vehicles – Similarly, rearming and refuelling on the go would

be quite different for different options

30/04/16 dkh©2004 30

Synergy

Worldmodels

Formationcontrol

Sensor systems



Weapon systems

Tacitknowledge

CognitionNature


Ethics andmorals

DoctrineMotivation

Experience

MissionManagement

Missionmanagement

BehaviourBehavior

Form Form

ViabilityManagement

Viabilitymanagement


management

Acquire

Store

Distribute

Convert


Homeostasis

Maintenance

Evolution

Constraint

Stimulation

Resourceenvironment









R.A.S.P.

Decision making

Assess situation



Decisionmode


Simulatementally

Y

N


Select preferred

option


Naive decisions

Monitor


Behaviorselection

Generateall options

Survival


Resourcesdisplays

Formationdisplays

Synergy

Worldmodels

Formationcontrol

Sensor systems



Weapon systems

Tacitknowledge

CognitionNature


Ethics andmorals

DoctrineMotivation

Experience

MissionManagement

Missionmanagement

BehaviourBehavior

Form Form

ViabilityManagement

Viabilitymanagement


management

Acquire

Store

Distribute

Convert


Homeostasis

Maintenance

Evolution

Constraint

Stimulation

Resourceenvironment









R.A.S.P.

Decision making

Assess situation



Decisionmode


Simulatementally

Y

N


Select preferred

option


Naive decisions

Monitor


Behaviorselection

Generateall options

Survival


Resourcesdisplays

Formationdisplays

Let Battle Commence…!

…but just a minute…

Blue Land Force 2010

Red Land Force 2010

30/04/16 dkh©2004 31

We Don’t Know Enough

•  We don’t know anything about our supposed enemy

•  We don’t know much about out own forces future beliefs and behaviours, training, etc.

•  How can we possibly fill in the details necessary to make the simulation work sensibly?

30/04/16 dkh©2004 32

Strengths of the Approach •  All true—but no reason to cop out •  First, and initially, it is sensible to assume

that an enemy is neither inadequate, nor a giant in ten-league boots.

•  It is sensible, as a start point, to assume that Red is as capable as Blue.

•  Then, we can assume, too, that Red ethics, morals, behaviours, training, etc., are the same as Blue’s, even if we are not too sure what Blue’s are

30/04/16 dkh©2004 33

So… •  In the first instance, create Blue from your

own designs, filling in parameter values from knowledge, experience or SWAG – Employ appropriate, trusted weather and radio

transmission models, typical Rx/Tx sensitivities & powers, and so on

– Having created Blue, replicate to create Red and couple so that the sensors and weapons of Blue seek Red and vice versa.

– Run the model. First run should be a standoff, with both parties inflicting and receiving equal damage (e.g. averaged out over, say, 1,000 runs)

30/04/16 dkh©2004 34

Wheatstone Bridge? •  In a sense, the two interacting models operate

like a Wheatstone Bridge (look it up!)

– Things that we may not know about in both Blue or Red tend to cancel out

–  If we think,say, ethics, may be a showstopper, then we insert the same model element for ethics on both sides:

•  No difference. However… •  Change Blue Ethics and the effects of “just and only”

ethics on operational effectiveness may be observed •  If it is minor, then ignore •  If it is major, then we need to know—research!

30/04/16 dkh©2004 35

Blue & Red Firing Patterns

4:28 PM Wed, May 31, 2000

Firing

Page 20.00 25.00 50.00 75.00 100.00

Time

1:

1 :

1 :

2 :

2 :

2 :

3 :

3 :

3 :

0.00

25.00

50.00

0.00

4.00

8.00

1: Weapons Display 2: Naive Decision Out[Fire Weapon] 3: RPD Decision Out[Fire Weapon]

1 1 1

1

2 2 2 23 3 3 3

•  Combatants close, engage, continue closing •  Initially “work out” firing opportunities (pink, using logic) •  Eventually just fire as fast as possible (green, using

experience‚RPD)

30/04/16 dkh©2004 36

•  Establish a scenario –  E.g. 2 identical land forces, 100m separation, engaging, weather

•  Install identical technology –  Radars, jammers, ESM, navigation, engines, weapons, situation

displays, battle damage displays, formation control, maintenance, etc.

•  Install identical people –  Training, cognitive abilities, experience, learning capability,

behaviour, etc. •  Establish identical C2 processes

–  Assess situation, identify threats, etc. –  Make decisions—engage, withdraw, fire, repair damage, etc.

•  Underpin with comprehensive cost models –  Capital, maintenance, operating, damage repair, people…costs

Using the Model—1

30/04/16 dkh©2004 37

Using the Model—2 •  Identical forces engage, score identical results

– Cost effectiveness, cost-exchange ratios, casualty exchange ratios

•  Hold one force constant. Change only one item on other force, say active radar transmitter power

•  Run model again – Any difference in results due to single change ∴ changing Tx power makes… δE difference to

overall effectiveness (E) •  in that scenario against that opposition

•  Takes account of all interactions, dynamics, costs

30/04/16 dkh©2004 38

Effectiveness is Emergent Effectiveness—COTS Vs.Bespoke Weapon

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9

Time

1

1.05

1.1

1.15

1.2

1.25

1.3

1.35

1.4

1.45

Blue Cost Effectiveness Red Cost Effectiveness Cost Exchange Ratio

Separation (nm)30.4 23.8 17.8 12.4 8.2 8.2 8.2 8.2 8.2

Equal time intervals

Red Force —Bespoke

Weapon

Blue Force —COTS Weapon

30/04/16 dkh©2004 39

Using the Model—3 •  Can optimize one force’s technology:—

–  Against given opposition in given scenario

•  Vary performance of each component up—measure—down—measure and restore

•  Repeat for all components—install single change that made biggest increase in, say, cost effectiveness

•  Repeat process until no further increase (20-30 cycles?) •  Process is cumulative selection. •  Result is optimum set of technologies,

–  with ideal MOPs = requirements?

30/04/16 dkh©2004 40

Test Bed •  The Interacting Blue Red Force Model

becomes a test bed: what are… – Effects of training on Effectiveness? – Can a smarter missile make up for not-so-smart

operators/decision-makers? – Effects on Effectiveness of increasing active

radar power? – …carrying more/less weapons – Etc., etc.,

•  Possible to ratchet overall design, too.

Increasing Blue Tx Power

0.7

0.75

0.8

0.85

0.9

0.95

1

1.05

1.1

1.15

1.2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Increasing Radar Tx Power

Casualty ER Poly. (Casualty ER) Establishing Requirements

•  Model indicates optimum radar Tx power

• too low, cannot detect target

• too high alerts enemy ESM

•  Sound approach to establishing MOPs and Requirements •  Views radar in context as part of C2 system, in combat,

interacting with other systems—including Red systems! •  Not in isolation as a disconnected building block

Casualty Exchange Ratio

30/04/16 dkh©2004 42

Identical Combatants—Caution!

•  Each MoE is a complex emergent property

•  Combat unpredictability makes them more so!

•  Not a simple weighting and scoring game! 0

50

100

150

200

250

300

350

0 10 20 30 40 50 60 70 80 90 100

Blue Cost Effectiveness Distribution

0

50

100

150

200

250

300

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

Cost Exchange Ratio

0

50

100

150

200

250

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

Casualty Exchange Ratio

Optimize System Design - Hitchinssystems.hitchins.net/.../incose-tutorial/optimize.pdfOptimize...

Documents

Transcript of Optimize System Design - Hitchinssystems.hitchins.net/.../incose-tutorial/optimize.pdfOptimize...