Whole Fleet Management The Barbican, East Street, Farnham, Surrey GU9 7TB 01252 738500 www.Advantage-Business.co.uk Advantage Programme Manager: Karen.

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Presentation transcript:

Whole Fleet Management The Barbican, East Street, Farnham, Surrey GU9 7TB Advantage Programme Manager: Karen Sparks Creating the Business Case Deciding which models/methods to use Karen Sparks MSc The views expressed in this presentation are those of the author and not necessarily those of the Whole Fleet Management Integrated Project Team

ISMOR Whole 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.

ISMOR Concept Reduced Unit Holding WFM Pooled Equipment U TPs OPs Training fleets/pools Operational fleets/pools U U U U U U U Unit holdings

ISMOR Analysis Issues/Agenda  This presentation focuses on OA/OE issues related to the assessment of WFM options:  Original modelling intent  The option down-selection process  Handling of future uncertainties  Revised modelling intent

ISMOR The 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.

ISMOR Cost Effectiveness OE Unit Holdings Pool Holdings Equipment Transactions Equipment Movement Repair and maint. change Infrastructure Requirements Manpower Requirements Transportation Requirements Cost

ISMOR Simulation n1 Equipment 1 n2 Equipment 2 n3 Equipment equipment types ~40,000 equipments > 24,000 modelling events Directed Training Plan 2002 Location Unit 1 Unit units Training Activity

ISMOR  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

ISMOR GA – Two options

ISMOR Step-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(N i )  Constraints included: N i – D ij ≥ 0 for all i,j i pool locations; j days

ISMOR Problem Reduction  For much of the year, the constraint N i – D ij ≥ 0 would not affect the solution.

ISMOR Step-wise LP/IP: Steps 2 and 3  Step 2: Minimise movement  Key constraint is that the total number of equipments must not exceed that determined by Step 1.  Step 3: Minimise cost  Key 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.

ISMOR Step-wise LP/IP Results

ISMOR Geographic Demand NB. Not valid to compare the actual numbers between the GA runs and LP/IP runs

ISMOR Uncertainty  Simulation model is data hungry and specific.  Nature of simulation makes uncertain futures difficult:  Future Army Structures  Garrison locations  Training regimes  Future equipment around  Related business initiatives  Analysis of trends using detailed event logs and influence mapping.  Military Judgement Panel.

ISMOR Use of Event Log Geographic demand for an option: by unit location; by training location Change in transportation: equipment, personnel Transactions: between units, unit-pool

ISMOR MJP  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.

ISMOR Down-selection Summary

ISMOR Lessons - 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.

ISMOR WFM Toolkit LP/IP optimisation Event log analysis MJP Benefits mapping Influence mapping (futures) GA optimisation Information to select the best solution Simulation database SIMULATION HR study

ISMOR END of presentation Questions ?