View
217
Download
1
Category
Tags:
Preview:
Citation preview
Model-Based Design of High-Performance Model-Based Design of High-Performance Command & Control OrganizationsCommand & Control Organizations
Daniel SerfatyDaniel SerfatyAptima, Inc.
Modeling of C2 Decision Processes WorkshopVienna, VA, Jul 31-Aug 2, 2001
Serfaty@aptima.comwww.aptima.com
12 Gill Street, Suite 1400 Woburn, MA 01801
(781) 935-3966 Ext. 211
1030 15th St NW, Suite 400 Washington, DC 20005 (202) 842-1548 Ext. 211
Objective
Demonstrate the potential of advanced organizational and team modeling techniques and tools to support:– Model-based experimentation – C2 Design decisions
Outline of Presentation
Value of modeling C2 Organizations– Prescriptive vs. descriptive modeling– Model-Based Experimentation
TIDE modeling approachC2 Design ExampleHow to use TIDE products
Virtual,Virtual, Human-in-the-Human-in-the-
Loop ExperimentsLoop Experiments
ConstructiveConstructiveSimulationSimulation
FieldField Applications, Applications,
LiveLive Assessment Assessment
EVENTS
TEAM LEADER'SWORKSTATION
MULTI-CHANNELCOMMUNICATION LINK
"WORLD"EVENTS
JAOCJAOC
WOC AWOC A WOC BWOC B WOC CWOC C
ElectronicElectronicTriadTriad
ElectronicElectronicTriadTriad
DM0
Sea-Mines& General Defense (Sea + Ground):artillery+hostile air+frog-launchers+etc.
DDG-003S M C-007
DM5
Hill + Beach A + Port
IN F ( A A A V )CA S
INF (M V 22)
DM4
Beach B + Airport
INF (A A A V )CA S
IN F ( M V 2 2 )
DM3
Medevacuation
M E DM E D
LHA -004LPD-005
DM2
lead-vehicle+Bridge+ground mines+SAM sites
CA S
E NG
S OF
S A T
B A S E -008
DM1
Defend North& DefendSouth
V F
S D
CG-001V FV F
FFG-002
CV -000
A A A VA A A VM V 22
M V 22
M E D
Rigorous human modeling• Algorithm-based team design• Human decision maker models• Simulation-based assessment
Simulation-based experimentation
• Team-in-the-loop simulation• Partnerships with academia and
industry• Technologies support data
collection & analysis
Live Performance Assessment & Human Engineering
• Computer-based observer tools• Results inform training, performance,
display design
Understanding Command Teams: From the Lab to the Field... And Back…
Why Design C2 Teams?
Engineering the interplay between the command organization’s systems & procedures and its human decision-makers to optimize the quality of decisions
Complex human-system design issuesHow many operators/decision-makers?
How to partition command roles?
How to distribute tasks among operators?
What is the optimal team structure?
How should operators proceed within it?
How will new technology and missions impact an evolutionary team design?
Goal: Leverage C2 Research to Improve Teams & Technology
Assess/diagnose team performance
Design teams & procedures
Design systems & interfaces
Design team training
Team Research
The Challenge (JTF example)
How would you derive human requirements for the organization?
How would you evaluate its performance for this mission?
How would you design a command team organization for this mission?
AEW of ERS
ATTACK NAVAL BASES
ATTACK CDCM
ATTACK RED IADS
ISR Surveillance YSEA
CVBG penetrate ERSTAMD ERS
TAMD YSEA
TAMD Island O
MIW in TSUS Strait
ATTACK AIR BASES
MINE RED PORTS
DESTROY C2 NODES
ISR Surveillance ERS
USW ERS
ASuW ERS
USW TS area
Surveillance COAST
AEW O
Defend vs. CDCM
CONT
CONT
CONT
CONTCONT
CONT
CONT
CONT
45 DAYS
7 DAYS
7 DAYS
45 DAYS
30 DAYS
5 DAYS
24 HOURS15 DAYS
7 DAYS
30 DAYSAEW of SOG
TAMD Blue
MIW in TSUG StraitNegate RED subs
Defend vs. CDCMSurf Survellance SOG
ATTACK RED AIR BASES (incl. BDA)
ATTACK RED C2 NODES (incl. BDA)
ATTACK RED IADS (incl. BDA)
ATTACK RED MSL BASES (incl. BDA)
CVBG penetrate SOG
TAMD protect Green
sensorshigh flyers low flyers, incl self defense
USW sanitization in A
5 DAYS
CONT
10 DAYS
30 DAYSCONT
CONT
CONT
24 HRS
30 DAYS
45 DAYS
AREA A OPS
AREA B OPS
Phase II OPS
Model-Based Experimentation:Design-Model-Test-Model
Adaptive Architectures for Command and Control (A2C2) ProjectIntegration of Modeling, Simulation, and Experiments
A Paradigm for Future Joint Experimentation?A Paradigm for Future Joint Experimentation?
Define Mission,
Objectives, Resources
Organization Design Process Experiment
Design
Conduct Experiment
Analyze Data Results
Pre-Exp. Model
Post Exp.
Model
Design Model Test
Scenario
AAR
Propose Hypotheses for Next Experiment
Refine Design
Validate
Model
Key Learning Loops
Example: JTF Model-Based “Optimized” Command Teams
FLAG
SAT-006BAS-008• SOF on BASE• CAS on (GREENs)CV• ENG on (BLUEs)LPD
GREEN
CV-000• VF on CV• VF on CV• VF on CVCG-001FFG-002DDG-003SMC-007
BLUE
• CAS on (GREENs)CVLPD-005• MV22 on LPD• • INFh on MV22• AAAV on LPD• • INFa on AAAV• MED on LPD
PURPLE• CAS on (GREENs)CVLHA-004• MV22 on LHA• • INFh on MV22• AAAV on LHA• • INFa on AAAV• MED on LHA• MED on LHA
Net 1
FLAG
GREEN
CV-000• VF on CV• VF on CV• VF on CVCG-001FFG-002
DDG-003SMC-007
BLUE
SAT-006BAS-008• SOF on BASE• CAS on (GREENs)CV• ENG on (PURPLEs)LPD
LHA-004LPD-005• MED on LHA• MED on LHA• MED on LPD
PURPLE
RED
• CAS on (GREENs)CV• MV22 on (PURPLEs)LPD• • INFh on MV22• AAAV on (PURPLEs)LPD• • INFa on AAAV
ORANGE
• CAS on (GREENs)CV• MV22 on (PURPLEs)LHA• • INFh on MV22• AAAV on (PURPLEs)LHA• • INFa on AAAV
Net 1
Net 2
A1-6: 6 nodes
A1-4: 4 nodes
Can Model-Based Designs Can Model-Based Designs Improve on Common Sense? Improve on Common Sense?
Experiments validate model-based team organizational design approach
Model-reduced
50 10060 70 80 9050 10060 70 80 90
Model-based
85.1 78.1
Ad-hoc79.7 59.7
76.2 68.5
Ove
rall
Mis
sio
n O
utc
om
e
Ob
serv
er’s
Ove
rall
Rat
ing
Design
Improved Team Process Performance
Findings-- Model-based architectures required less communication-- Engineered capabilities at each command node reduced wasteful inter-node coordination-- Better and more timely use of communication channels supported anticipatory behavior (a performance predictor)
Ad-hoc Model-based Model- reduced0
1
2
3
4
5
6
7
8
Co
mm
Rat
e [m
sgs/
min
]
0
0.5
1
1.5
2
2.5
3
Co
ord
inat
ion
Act
ion
s [/
min
]
Model- reduced Model-basedAd-hoc0
1
2
3
4A
nti
cip
atio
n R
atio
Model-reduced Model-basedAd-hoc
Limited-Objective, Model-Based Experimentation (A2C2/GLOBAL ’99)
Feedback, Learning
Field Test Org. Designs
“Bridge”“Bridge” GLOBALWargame
GLOBALWargame
Adaptive Architectures for Command and
Control (A2C2)
Adaptive Architectures for Command and
Control (A2C2)
Network Centric Warfare
Network Centric Warfare
Design of Command Orgs.
Model-Based Experimentation Opportunity to
“Port” A2C2 Innovation to Warfighters
Innovative Organization to
Test NCW Concepts Effects-Based
Operations
Network Centric Warfare
Info. Tech: IT21
Model-Based Team Architectures
ALPHA CHARLIE BRAVO
FLAG
Phase I
ALPHA
CHARLIE BRAVO
FLAG
Phase II
ALPHA, BRAVO, and CHARLIE cells are multi-functional, multi-service sub-teams
coordinationcommand or supported/supporting
Adaptation
“Bridge” Example: Phase I Architecture
FLAG
CHARLIEALPHA
BRAVO
Assets1 CVN(X)1 DDG1 CG1 JSTARS2 MH-531 MCM24 P3C3 SSNRC-135s…
Area of OperationsYSEA , ERS , I.O
CVN penetration, ASuW, MIW + Attack
Mission Tasks• Surface Surveillance of ERS, YSEA, and island O• Defense vs. CDCM Attack• USW in ERS, YSEA, and island O• ASuW in TSUS area• MIW in TSUS Strait• CVBG penetrates ERS
In addition, Bravo is/can be involved in the following tasks:
• Attack Naval Bases from ERS• Attack Red C2 Nodes from ERS (together with Charlie)• Attack Red IADS from ERS (together with Charlie)• Attack Red Missile Bases from ERS (together with Charlie)
Team Modeling for C2 Organizations
to support
• Planning• Direction• Control • Coordination
• Joint operations• New technology• Rapid response• Unpredictability
CurrentResponsibilities
OperationalChallenges
require
• Adaptability • Flexible structures• Inter-operability• Optimized communication
OrganizationalNeeds
Team/Organizational Modeling produces organizationalstructures that are “congruent” with mission needs
Questions
Designing an Organization
Who does what?Who controls what?Who sees what?Who knows what?Who talks to whom?Who gives orders?Who makes decisions? Who overrides decisions?
Str
uc
ture
Who is responsible for what?Who is tasked with what?Who backs-up whom?Who talks with whom? Who coordinates with whom?P
roc
ess
Allocation- Resources- Information- Communication- Command
Scheduling- Functionality- Tasks- Coordination- Back-up
Method Outcomes
OptimalProcess
OptimalStructure
Optimal Structure
Optimal Process
Can the structure sustain the C2 process?
What effect the process has on the organization?
Mission Structure
OrganizationalConstraints
Problem Formulation as Multi-Objective Structural and Process Optimization
Defining Organizational Design
What can be replaced by what
Team Organizational Design
Who talks to whom
Who does what
Resources
What it takesto complete
HumanDecision-MakersWho owns what &
Who knows what
Tasks
Mission
RESOURCEALLOCATION
TEAM STRUCTURALENGINEERING
FUNCTIONALLOCATION
MISSION ANALYSIS
Mission-Based Methodology for Modeling Organizations
FE
ED
-BA
CK
FE
ED
-BA
CK
Iter
ativ
e D
esig
n P
roce
ss
Organizational Design Process1) Task to Resource Allocation2) DM to Resource Allocation3) Organizational Structure
Organizational Constraints
Team/System Capabilities
Quantitative Mission Structure
Task Requirements
Multi-Dimensional Task DecompositionMissionMission
Organizational Structure1) Taskwork Strategy2) Teamwork Strategy3) Physical Lay-Out Performance
Measures
T
R DM
Outline of Presentation
Value of modeling C2 Organizations– Prescriptive vs. descriptive modeling– Model-Based Experimentation
TIDE modeling approach
C2 Design Example
How to use TIDE products
TIDE: Organizational EngineeringTeam Integrated Design Environment
Mission-driven organizational design process
A novel, formal, and quantitative way to model teams and organizations– Prescriptive methodology– New technology/automation tradeoffs– Cost and risk reduction
Multiple optimization criteria– Error minimization, workload balance, speed, etc…
TIDE is capable of supporting the design of both revolutionary and evolutionary organizational structures
to support optimized mission performance
Examples of C2 Organizational Design Objectives
Speed of Command – Organization must meet mission objectives at maximum
speed of command (--> op tempo)
Staff Reduction – Reduce Command Staffing by X%
Acceptable Workload – Minimize Peak Workload/Balance Workload– Total Workload Accumulation
Effective Team Coordination – Optimize inter-node synchronization– Minimize communication message queues
TIDE Five-Phase Process
Phase A:Mission
RepresentationPhase B:
Task-ResourceMapping
Phase E:Organizational
Structuring
Phase C:Clustering Tasks
into Roles
Event-Task Mapping
Optimized TaskScheduling
Operator Role Definition/Info Requirements
Team-LevelAssignments
Team DesignStructures
+ Processes
Design Objectives,
Criteria,Constraints
Phase D:Design Team Interactions
Phase A: Mission Representation
Phase A:Mission
Representation
Tasks Tasks (Required (Required
responses)responses)
Scenario Scenario EventsEvents
Response Response CriteriaCriteria
Stochastic Stochastic Mission Mission ModelModel
Event to Event to Task Task
MappingMapping
CategorizationCategorization
Representing the Mission
Task interdependencies
External triggering events
Multiple scenarios that represent extremes for mission performance
Resources required for each task & effectiveness of resource packages
Duration and workload associated with tasks
air-defenseNorth
AirportAirport
suppress airportSAM-sites
North roadground mine PortPort
suppress portSAM-sites
suppress submarines
air-defenseSouth
Hill Hill hill
sea-minesholdhill
Beach BBeach Bbeach B
sea-mineshold
beach B
Beach ABeach Abeach A
sea-mineshold
beach A
detect & eliminate
lead vehicle BridgeBridge
South roadground mine
medicalevacuation
generaldefense
artillerytanks
hind-hellosfrog-launchers
hostile air silk-wormspatrol boats
* Navy/USMC J oint scenario (North Africa circa 2005)
Subject matter experts define the mission
Note: In this phase, TIDE can take advantage of an existing Mission model (IDEF, Task Network, Petri Net, Simulation model, etc…)
Event-to-Task Mapping
Issue_Level_1_Query
Conduct_Engagement_with_Birds
Respond_to Air_Threat
Conduct_Threat_Assessment
UAE_within_40_NM_of_USN_Surface_Ships
UEV_within_40_NM_that_prompts_self_defence
Air_Warfare_Commander_order_to_issue_Level_II_warning
Issue_DMZ_Violation_ReportMonitor_Airspace_Compliance
Track_approaching_DMZ
Track_in_violation_of_DMZ
Plan/Configure_for_Air_Defense_MissionConfigure_Watchstation
Review_Systems_Status
Monitor_Air_Situation
Log_in
Delouse_Aircraft_RTF
Need_to_delause_A/C
UAE/UEV_closing_within_60_NM_of_USN_Surface_Ships
UEV_within_40_NM_of_USN_Surface_Ships
Review_and_Respond_to_ESM_Information
Correlated_ESM
Correlated_95%_ESM
Uncorrelated_ESM
Review_ID_Indicators
UEV_closing/is_within_75_NM_of_CV
Issue_New/Update_Track_Verbal_Report
UEV
UAE
Maintain_Ownship_SA
External_Comm
Clear_Aircraft_Departing_CV
A/C_requests_permission_to_proceed_to_RTF
Monitor_Team_Workload
Workload_of_a_watchstander_too_high
Conduct_DCA_Intercept_&_Escort
Control DCA
UAE_closing_within_75_NM_of_CV
UAE_is_within_75_NM_of_CV
New_Air_Contact_Radar_Detection(Com_Air_track)
New_Air_Contact_Radar_Detection(Enemy_track)
New_Air_Contact_Radar_Detection(Enemy_track)
Phase B: Optimal Task Scheduling
Meet time constraints
Maximize effectiveness
Resolve resource contentions
Mission Schedule
Multi-objective optimization algorithms to develop optimal schedule:
Note: Roles for individuals not yet considered
1. Optimal branch-and-bound algorithm
2. Dynamic Programming algorithm
3. Dynamic List Scheduling (DLS)
4. Pair-wise task exchange
Phase C: Cluster Tasks Into Roles
Typically optimize for:– balanced workload across
individuals
– minimize need for coordination and communication
Constrain using individual workload ceilings
Results are fed back to task scheduling
Multi-dimensional multi-objective clustering algorithms leading to task-resource pairs:
Team size is either given or optimized
Multi-dimensional Clustering AnalysisEx: Cluster on Information
Location(A/C)
Conduct_DCA_Intercept_&_Escort
Issue_Level_1_Query
Clear_Aircraft_Departing_CV
ID(Track)
Range(Track,USN_Ship)IFF(A/C)
Engagement_solution
Engagement_order
IFF(Track)
Location(Track)
Review_ID_Indicators
Respond_to Air_ThreatConduct_Threat_Assessment
Issue_DMZ_Violation_ReportControl DCA
Conduct_Threat_ Assessment
Conduct_Engagement _with_Birds
Control_ DCA
Review_ID_ Indicators
Location(A/C) 0 0 1 0Location(Track) 1 1 1 1Range(Track,USN_ships) 1 1 0 0Engagement_solution 1 1 0 0Engagement_order 0 1 0 0IFF(A/C) 0 0 1 0IFF(Track) 0 0 0 1ID(Track) 1 0 0 1
Conduct_Engagement_with_Birds
Info
rmat
ion
feat
ures
• Goal: Maximize information within watchstanders; minimize info overlap when unnecessary• Conduct_DCA & Control_DCA use similar info; Review_ID & Conduct_engage-ment do not.
InfoTask
Phase D: Engineering Team Interactions
Uniquely assign tasks when possible to minimize routine communications between team members
May need to split tasks if individuals are overloaded
Detailed Modeling Tool:
Note: Splitting tasks introduces new communication workload
Information Variables
Decision Variables
Action Variables
Outcome Variables
Initiate/Confirm Engage Order
Engage_with_Birds
In-boundmissile msg
ROE
Track’s failure torespond to Level II Warning
Track’s failure torespond to Illumination
System Status
Track Verbal Report
Engagement Status
Weapons Away (Y/N?)
Engagement OrderKill Evaluation (Y/N?)
‘Initiate/ConfirmEngagement’Msg
‘Produce EngagementSolution’Msg
‘Weapons Ring’Msg
‘Issue Track Report’Msg
‘Kill Evaluation’Msg
Release Missiles
Track’s visualdisplay profile Track is covered (Y/N?)
System’s movingtwds releasing Weapons (Y/N?)
Firing Solutionstill a go (Y/N?)
In-boundMissile (Y/N?)
Track’s meetingROE (Y/N?)
Track’s approachingits weapons range (Y/N?)
Initiate Engage Orders (Y/N?)
Engagement Solution
WeaponsAway Yes
Kill Yes
Track is covered
System’s movingtwds releasing Weapons
Firing Solutionstill a go Yes
Engage OrdersInitiated
Firing Solutionno longer a go
System’s failed inmovingtwds releasingWeapons
Engage OrdersNOT Initiated
Track is NOT covered
WeaponsAway No
OUTCOME Variables
DECISION Variables
INFORMATION Variables
ACTION Variables
OUTCOME Variables
DECISION VariablesINFORMATION Variables
ACTION Variables
Respond_to_air_threat
Evaluate_threat
Intra- and inter-task analyses suggest opportunities to combine tasks into roles
3
2
Intra- and Inter-Task Analysis
Example Objective: Balancing Workload in the Team
Instant Workload
0
Threshold
)()(max0;
maxargmax tWtW iDMiDM
ttAEGISiDMMMWSiDM
Objective 1:
min)(
)(
max
max
0
0
minarg
maxarg
tt
iDM
tt
iDM
tW
tW
MMWSiDM
MMWSiDM
Workload AccumulationBalance
DM1 DM2 DM3 DM4 DM5
1 101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Team Leader
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Air Coordinator-
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Watchdog
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Information Coordinator
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Battle Manager
Notional Workload Analysis
Outline of Presentation
Value of modeling C2 Organizations– Prescriptive vs. descriptive modeling– Model-Based Experimentation
TIDE modeling approach
C2 Design Example: AWACS
How to use TIDE products
AWACS Design Challenge
TIDE Design Approach Mission analysis
What needs to be done What information is available
Task analysis How is it done What information is used
Organizational analysis How is information shared Who does what
How do you design an optimal command & control teams for complex, variable AWACS missions to take advantage of advanced information fusion technology?
Example: AWACS Crew Optimization
Human-Centered Re-Engineering of AWACS Command and Control Teams (REAC2T)– Phase III SBIR Project funded by AWACS System Program
Office ESC, Hanscom AFB
Demonstrate proven, scientific approach to C2 team design in AWACS domain– Team Integrated Design Environment (TIDE)
Present ACC/Wing with proof-of-concept for crew optimization– Evaluate impact of information fusion on mission performance
and operator functions– Introduce optimized team structures to enhance mission
performance
AWACS Example: Inputs to Mission Model
Mission decomposition and evaluation– Work with operational community to define current approach to
mission completion• CONOPS, tactics, roles, and responsibilities
Red Flag Spin-Up Training– Tinker AFB
Live Fly Red Flag Exercises– Five flights, Nellis AFB
Cognitive Task Analysis– Wing Tactics Office, Tinker AFB– SD instructors Fighter Weapons School, Nellis AFB
TIDE Prototype Software
Mission & task graphs are converted into data tables to serve as input for optimization algorithms
Preliminary Results: Baseline 14 Operator Task Distribution
Colors represent unique operational tasks
Max Workload = 1400
Impact of Technology (MSI) Insertion:Non-Optimized 14 Operator Configuration
Colors represent unique operational tasks
Max Workload = 950
Impact of Technology (MSI) Insertion:Optimized 14 Operator Configuration
Colors represent unique operational tasks
Max Workload = 750
Impact of Technology (MSI) Insertion:Optimized 12 Operator Configuration
Colors represent unique operational tasks
Max Workload = 800
Internal Communication: Outgoing Messages
MSS W1S W2 W3 W4 W5 W6 S1S S2 S3 S4 S5 0
20
40
60
80
100
120
140
DMs
Out
goin
g M
essa
ges
MCC SD STK OCA Chk_In HVAA STK_Ast OCA_Ast ASO ECO AAST AST_1 AST_2 AST_3 0
20
40
60
80
100
120
DMs
Out
goin
g M
essa
ges
Baseline
MCC SD STK OCA Chk_In HVAA STK_Ast OCA_Ast ASO ECO AAST AST_1 AST_2 AST_3 0
50
100
150
200
250
300
350
400
450
500
DMs
Out
goin
g M
essa
ges
MSI Non-Optimized 14
MSI Optimized 14 MSI Optimized 12
MCC SD STK OCA Chk_In HVAA STK_Ast OCA_Ast ASO ECO AAST AST_1 AST_2 AST_3 0
20
40
60
80
100
120
140
160
DMs
Out
goin
g M
essa
ges1. Technology1. Technology
InsertionInsertion
500 160
3. Manning 3. Manning OptimizationOptimization
2. Optim
al
2. Optim
al
TeamTeam
Summary: Model-based Re-Engineering of AWACS Command & Control Teams (REAC2T)
T91 -Recordkeep - Significant
events
T76 - Provide C2for workaroundsto appropriate
players
T75 - Coordinatewith senior C2
elements
T74 - Define/recommend
missionmodifications
T71 - Define whatis needed to
continue/complete mission
T62 - Send anarrow
T60 - Broadcastnew information
T57 - Requestsupport fromsupervisorT47 - Distribute
mission status
T46 - Providevector information(i.e. refueling, flight
join, airspace)
T43 - Respond torequests for
information (RFI)
T42 - Makepicture calls
T26 - Identify airthreats
T24 - Provide allavailable amplifyinginformation (tracks)
T20 - Utilizeorganic radar
data
T19 - Fuse datafrom multiple
sources to locateobjects (detect)
T7 - Reconfigureradar for
changing missionobjectives
T102 - Receiveinformation from
pilots
T45 - Monitorairborne assets
missionreadiness
T48 - Assessfighter fuel level
T103 - Pullinformation from
pilots
ANDOR
AND
OR
AND
AND
OR
AND
A17 - Fuse data frommultiple sources toensure tracks are
correct
A12 - Detectnew track
D28 - Determinewhere you shouldanticipate a threat
D16 - Decidewhat is a valid
air object (track)
I17 -Intelligence
dataI4 - ATO
I64 - RadarData
I65 - IFFData
I66 - ESMData
I67 - OtherSensor
A2 - InitiateTrack
SymbologySwitch Action
AND
O39 - Tracksymbology
I56 - Trackposition
Re-engineering based on AWACS mission task models Scientific C2 team design approach to AWACS domain: TIDE
-Team Integrated Design Environment Org. design for new technology insertion and optimized manning
0
2
4
6
8
10
12
Baseline New Tech Only
New Tech + Optimized 1
New Tech + Optimized 2
Crew Configuration
Ave
rag
e T
ask
Del
ay
(se
co
nd
s)
Task Model
Faster Teams
Outline of Presentation
Value of modeling C2 Organizations– Prescriptive vs. descriptive modeling– Model-Based Experimentation
TIDE modeling approach
C2 Design Example
How to use TIDE products
TIDE Model Products
Mapping of Tasks to Team Members
Task Cluster Output
DM1 DM2 DM3 DM4 DM5
Configure_Watchstation 1 1 1 1 1
Plan/Configure_for_Air_Defense_Mission 1 1 1 1 1
Review_Systems_Status 1 1 1 1 1
Issue_Level_1_Query 0 0 1 0 0
Respond_to_Air_Threat 1 0 1 1 0
Conduct_Engagement_with_Birds 1 0 0 1 0
Review_ID_Indicators 3 1 2 2 4
Issue_Update_Track_Verbal_Report 0 0 0 1 0
Conduct_DCA_Intercept_&_Escort 1 0 0 1 1
Issue_DMZ_Violation_Report 2 1 1 1 1
Clear_Aircraft_Departing_CV 0 0 0 0 1
Team Descriptions
4.0
4.1
4.2.1 4.2.2
4.3
CAS (8)
CV (1)
TARP (1)
Rifle Co (3)
Stinger (1)
4.2
Cobra (2)
Rifle Co (3)
Cobra (2)
Stinger (1)
Eng . (1)
MED (1)
MCM (1)
CG(1), DDG(2)
Eng . (1)
MED (1)
MCM (1)
VF(8), FFG(2)
Performance Predictions
1 101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Team Leader
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
AIC-REDCROWN
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Watchdog
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Information Coordinator
101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601
Battle Manager
Detailed Specification of Team Roles:
When Tasks are performed
How Decision are made
What Resources are used
What Information is used
What Communications are required
Multiple Applications of TIDE Model
EVENTS
TEAM LEADER'S WORKSTATION
MULTI-CHANNEL COMMUNICATION LINK
"WORLD" EVENTS
Synthetic Task Environments
TIDE Organizational Design Process
Phase A:Mission
RepresentationPhase B:
Task-ResourceMapping
Phase E:Organizational
Structuring
Phase C:Clustering Tasks
into Roles
Event-Task Mapping
Optimized TaskScheduling
Operator Role Definition/Info Requirements
Team-LevelAssignments
Team Design(Structures
+ Processes)
Design Objectives,
Criteria,Constraints
Design Objectives,
Criteria,Constraints
Phase D:Decompositionof Role Overlap
Organizational Design
Intelligent Agents
Training Programs
Tide Input Model
IDAO Decomposition
A31 - Target thethreat
D4 - Decidehow to use
available airand groundresources
O14 - Commit pairfighters
I49 - Fighterweapons
status
I19 - Missionrequirementsand priorities
I41 - Fighterfuel status
I51 - Threat/target
location
ANDI17 -
Intelligencedata
A22 - Monitor theair picture
IDAO Decomposition
Event-Task Mapping
Time on Target (ToT)
T36 - Maintainaccurate track /
symbologycorrelation
T19 - Fuse datafrom multiple
sources to locateobjects (detect)
T22 - Interpret /Filter information
T20 - Utilizeorganic radar data
T95 - Monitorairspace
T42 - Make picturecalls
T86 - Providetarget location
T43 - Respond torequests for
information (RFI)
T24 - Provide allavailable amplifyinginformation (tracks)
OR
T102 - Receiveinformation from
pilots
T56 - Receivemission effectiveness
/ BDA
T47 - Distributemission status
AND
Event-Task Mapping
Task Decomposition
ID/track air objects
Respond to threats
Record keeping
ASK FOR INPUTto ATSO (self-preservation)
Identify Threat type
Identify ThreatLocations
Direct weaponsto target/threat
Analyze system resourcesto locate jammers whileMonitoring system for jamming
Execute electronic countermeasures while Monitoringsystem for jamming
Broadcast jammer locationwhile Monitoring systemfor jamming
TCTC Mission
Define Threats
Decide to engage or not
Operate MCS systems
Surveillance/detectair objects
Create/maintain recognizable& integrated air picturePass/receive information
Manage ATO execution
ATSO (self preservation)Airborne (C2 of airborne assets)
Respond to Threats Respond to pop-up targets
Monitor system for jamming
ID/track air objects
Respond to threats
Record keeping
ASK FOR INPUTto ATSO (self-preservation)
Identify Threat type
Identify ThreatLocations
Direct weaponsto target/threat
Analyze system resourcesto locate jammers whileMonitoring system for jamming
Execute electronic countermeasures while Monitoringsystem for jamming
Broadcast jammer locationwhile Monitoring systemfor jamming
TCTC Mission
Define Threats
Decide to engage or not
Operate MCS systems
Surveillance/detectair objects
Create/maintain recognizable& integrated air picturePass/receive information
Manage ATO execution
ATSO (self preservation)Airborne (C2 of airborne assets)
Respond to Threats Respond to pop-up targets
Monitor system for jamming
Mission Decomposition
ID/track air objects
Respond to threats
Record keeping
ASK FOR INPUTto ATSO (self-preservation)
Identify Threat type
Identify ThreatLocations
Direct weaponsto target/threat
Analyze system resourcesto locate jammers whileMonitoring system for jamming
Execute electronic countermeasures while Monitoringsystem for jamming
Broadcast jammer locationwhile Monitoring systemfor jamming
TCTC Mission
Define Threats
Decide to engage or not
Operate MCS systems
Surveillance/detectair objects
Create/maintain recognizable& integrated air picturePass/receive information
Manage ATO execution
ATSO (self preservation)Airborne (C2 of airborne assets)
Respond to Threats Respond to pop-up targets
Monitor system for jamming
ID/track air objects
Respond to threats
Record keeping
ASK FOR INPUTto ATSO (self-preservation)
Identify Threat type
Identify ThreatLocations
Direct weaponsto target/threat
Analyze system resourcesto locate jammers whileMonitoring system for jamming
Execute electronic countermeasures while Monitoringsystem for jamming
Broadcast jammer locationwhile Monitoring systemfor jamming
TCTC Mission
Define Threats
Decide to engage or not
Operate MCS systems
Surveillance/detectair objects
Create/maintain recognizable& integrated air picturePass/receive information
Manage ATO execution
ATSO (self preservation)Airborne (C2 of airborne assets)
Respond to Threats Respond to pop-up targets
Monitor system for jamming
0 200 400 600 800 1000
Line1
T18T68T28 T20 T66 T70 T67 T69 T71 T28 T83 T83 T83
Line2
T18T18T28 T20 T37 T67 T69 T71 T95 T44 T71 T83
Line3
T18T20 T20 T67 T69 T71 T83
Line4
T18T18T18T18T20 T66 T69 T71 T44 T98 T70
Line5
T28T18T20 T20 T90 T67
Line6
T28 T20 T20 T92 T28 T83 T1
Line7
T28T18T20 T92 T28 T9 T83 T44 T83 T87
Line8
T18T18T18T20 T20 T65 T64 T69
Line9
T4T18 T66 T77 T70 T81 T69
Line10
T28 T20 T97 T83 T83 T83
Line11
T18T18 T16 T9 T83
Line12
T18T18 T16 T27
Line13
T18T28 T20 T2 T83
Line14
T20 T20 T37
Line15
T18T18 T20
Line16
T18T18 T20
Line17
T18T18 T20
Line18
T28 T20
Line19
T89
Line20
T20 T20
Line21
T16
Line22
T20 T20
Line23
T20
Time
C2 Process Re-engineering
Interface Design
Model-driven Measurement ProcessModel-driven Measurement Process
Learning Objectivesin JTF Environment
Competencies:Knowledge, Skills,and Abilities
Tasks
Scenario
Stimulated or Trained by...
Improve by X%
Put together into vignettes...
IndividualTeam
Team-of-Teams
Theories ofPerformance LinkSkills to Behaviors toTasks
Stories andevents
MOPs &Measurement
Tools
MeasurementChallenges
Performance Measures by TaskHow well did learners perform?
KSA AssessmentWhat KSAs do learners have/lack?Diagnose individuals’ needs for additional training
Success in Meeting Training ObjectivesHow well are training objectives met?Success at JTF; Certification
Subject Matter Experts
TIDE Model
TIDE Integrated Toolset
Task Network SimulationOrganizational Structure
Task Hierarchy
Assess platformneeded
Receiveplatform
status
Assess need torequest
Task
Platform, DM Platform
Task, Platform
Task, Platform
Task, Platform, DM
Decision-Maker Model
DESIGN
SIMULATION-BASEDEVALUATION
ANALYSIS
Team Optimal Design
(TOD)(TOD)T
DMR
User/SME input and review
MissionAnalysis
S u b 3
S u b 1 S u b 2
L ead
Sub 2Sub 3Sub 1
Leader
Computational Organization Model
50 10060708090
85.179.7
76.2
Mis
sio
n O
utc
om
e
Some Current Military Applications of the TIDE Modeling Methods and Tools
Joint Task Force Adaptive Architectures for Command and Control (A2C2)Next Generation Navy Surface Ships (SC-21/DD-21)Human-Centered Re-Engineering of AWACS Command and Control Teams (REAC2T)Uninhabited Combat Air Vehicle (UCAV) Control CenterKwajalein Radar/Missile Control Center (ATIDS)Air Operations for Time Critical Targets (JFACC)Time Critical Targeting Cell in Air operations (CAOC)Effects-Based Operations in Operations Center (EBO)Army Future Combat Systems (FCS)Global Wargame JTF Org. Design and Assessment….
Summary: Why Model C2?
TIDE is a method to optimize decision-making organizations to capitalize on advanced technology
Model-based organizational structures are “congruent” with mission needs
Modeling guides experimentation and performance assessment
Analysis and design tool for system designers– Cost and risk reduction
– New technology payoffs
Mission/organization model serves multiple purposes – Organizational design: Provide alternative, optimized organizations
– Team training: Highlight areas for team training
– Synthetic tasks: Develop environments to train and evaluate teams
– Interface design: Functional definition of GUI
Recommended