Whole Fleet Management

The Barbican, East Street, Farnham, Surrey GU9 7TB01252 738500www.Advantage-Business.co.uk

Advantage Programme Manager: Karen Sparks01252 738576karen.sparks@advantage-business.co.uk

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.

18

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 ?