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Whole Fleet Management
The Barbican, East Street, Farnham, Surrey GU9 7TB01252 738500www.Advantage-Business.co.uk
Advantage Programme Manager: Karen Sparks01252 [email protected]
Creating the Business CaseDeciding which models/methods to use
Karen Sparks MSc
The views expressed in this presentation are those of the authorand not necessarily those of the Whole Fleet Management Integrated Project Team
2
ISMOR 2005Whole Fleet Management
WFM is: The process of managing a fleet of equipment
through global visibility in the most supportable, effective and economic way in order to meet the stated operational, training and support requirements.
Whole Fleet Management (WFM) is essential because equipment is now procured in accordance with Total Fleet Requirement (TFR). Fleets in the future will be smaller.
3
ISMOR 2005Concept
Reduced UnitHolding
WFM
Pooled Equipment
U
TPs OPs
Training fleets/pools Operational fleets/pools
U
U
U
U
U
U
U
Unit holdings
4
ISMOR 2005Analysis Issues/Agenda
This presentation focuses on OA/OE issues related to the assessment of WFM options:Original modelling intentThe option down-selection processHandling of future uncertaintiesRevised modelling intent
5
ISMOR 2005The Business Case/COEIA
Objective is to analyse options and to define the most cost-effective solution:
Level of unit holding.Locations and sizes of pools.
…… assuming that today’s level of training is maintained.
6
ISMOR 2005Cost Effectiveness
OE
Unit Holdings
Pool Holdings
Equipment Transactions
Equipment Movement
Repair and maint. change
Infrastructure Requirements
Manpower Requirements
Transportation Requirements
Cost
7
ISMOR 2005Simulation
n1 Equipment 1n2 Equipment 2n3 Equipment 3
160 equipment types
~40,000 equipments
> 24,000 modelling events
Directed Training Plan
2002
LocationUnit 1Unit 2
163 units
Training Activity
8
ISMOR 2005
For each defined unit holding option:What is the best set of pool locations and pool
populations ?
Optimisation:Genetic algorithms (GA) with the simulation.Independent Linear Programming (LP/IP).
Goal
9
ISMOR 2005GA – Two options
4345
GA for 1 Sub CE
4345
GA for 1 Sub CE
323
1503
992
GA for ETF CE
323
1503
992
GA for ETF CE
10
ISMOR 2005Step-wise LP/IP: Step 1
Step 1 – Minimise total number of equipments required for training.
Unit holdings are fixed. So this is achieved by minimising the number of equipments in TPs for each equipment type:
MIN Σ(Ni)Constraints included:
Ni – Dij ≥ 0 for all i,j
i pool locations; j days
11
ISMOR 2005Problem Reduction
Germany
0
5
10
15
20
25
30
35
40
45
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360
actual
none
target
For much of the year, the constraint Ni – Dij ≥ 0 would not affect the solution.
12
ISMOR 2005Step-wise LP/IP: Steps 2 and 3
Step 2: Minimise movementKey constraint is that the total number of
equipments must not exceed that determined by Step 1.
Step 3: Minimise costKey constraints are:
The total number of equipments must not exceed that determined by Step 1.
Equipments cannot be located more that 100 km away from their location determined in Step 2.
13
ISMOR 2005Step-wise LP/IP Results
48
187
2072
LP for 1 Sub CE
247
13741
48
187
2072
LP for 1 Sub CE
247
13741
94
115
1121
154
137
LP for ETF CE
94
115
1121
154
137
LP for ETF CE
14
ISMOR 2005Geographic Demand
4345
GA for 1 Sub CE
4345
GA for 1 Sub CE
48
187
2072
LP for 1 Sub CE
247
13741
48
187
2072
LP for 1 Sub CE
247
13741
1 Sub option
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
Scotland NE NW E WM Wales HC SW
Num
ber o
f dem
ands
in re
gion
at t
rain
ing
area
A B C Z
NB. Not valid to compare the actual numbers between the GA runs and LP/IP runs
15
ISMOR 2005Uncertainty
Simulation model is data hungry and specific. Nature of simulation makes uncertain futures difficult:
Future Army StructuresGarrison locationsTraining regimesFuture equipment around 2015 +Related business initiatives
Analysis of trends using detailed event logs and influence mapping.
Military Judgement Panel.
16
ISMOR 2005Use of Event Log1 Sub option
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
Scotla
nd NENW E
WMWales SE HC
SW NI
Num
ber
of d
eman
ds fr
om u
nit's
reg
ion
A B C Z
1 Sub option
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
Scotland NE NW E WM Wales HC SW
Num
ber
of d
eman
ds in
reg
ion
at tr
aini
ng a
rea
A B C Z
0
200
400
600
800
1,000
1,200
1,400
1 Sub ETF (A) TE (A) ETF (All) TE (All) Hybrid (TE)
Dis
tanc
es /0
00s
km
UK Germany
-400
-200
0
200
400
600
800
1,000
1,200
1,400
1,600
1 Sub ETF (A) TE (A) ETF (All) TE (All) Hybrid (TE)
Dis
tanc
es /0
00s
km (D
elta
to 'D
o N
othi
ng')
A&CB
0
10,000
20,000
30,000
40,000
50,000
60,000
1 Sub ETF (A) TE (A) ETF (All) TE (All) Hybrid (TE)
Num
ber o
f equ
ipm
ent t
rans
actio
ns
Pool/Unit Unit/Unit Total
Geographic demand for an option: by unit location; by training location
Change in transportation:equipment, personnel
Transactions:between units, unit-pool
17
ISMOR 2005MJP
Flexibility for uncertain futures. and …
The simulation takes account of the equipment – but not the impact on command and control and human factors.
The optimisation focused the information on possible sites – but did not take account of wider issues.
Military judgement panel captured preferences in these areas.
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ISMOR 2005Down-selection Summary
1 Sub ETF (A) ETF (All) TE (A) TE (All) Hybrid (TE) Cost 1 4/5 5/4 3 2 6 Future equipment 3 6 2 5 1 4 Low unit holdings 6 5 3 4 1 2 High pool holdings 6 5 3 4 1 2 High OP holdings 4 6 3 5 1 2 6
Low transactions overall 2 3 6 1 4 5 5
Low inter-unit transactions 6 2 5 1 3/4 3/4 4
Low white fleet moves 6 3 5 1 2 4 3
Low equipment moves 6 5 4 1 2 3 2
1
Higher training potential 6 2 2 2 1 1 Greater FRC flexibility 6 5 4 2 1 3 Availability 5 6 3 4 1 2 Force generation 4 6 3 5 2 N/A
Best
Worst
19
ISMOR 2005Lessons - Balance
Single ‘all-in-one’ approach may hide business drivers.
Adding complexity (greater ‘realism’) may add little value.
Analysis of underlying trends leads to a better understanding than taking final outputs from a large number of simulation runs.
Optimisation needs to be used with care.
20
ISMOR 2005WFM Toolkit
LP/IP optimisation
Event log analysis
MJP
Benefits mapping
Influence mapping(futures)
GA optimisation
Information to select thebest solution
Simulation database
SIMULATION
HR study
21
ISMOR 2005END of presentation
Questions ?