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Maritime Logistics Community News : Summer 2010
32 NAVY SUPPLY NEWSLETTER SUMMER 2010 These tools are designed to reduce the Logistics Cost of Ownership (LCOO) for Navy -- the Maintenance, Analysis and Input Tool (MAIT ) and the Condition Based Maintenance (CBM) Toolkit. DSTO under the guidance of DGMARSPT has built on these smart maintenance initiatives with the development of the Mean Variance Tool (MVT) and combining it with MAIT to enable the making of quantitative and qualitative decisions within the one framework for the development of maintenance work packages. The preparation of work lists for maintenance availabilities of RAN platforms are currently undertaken using labour intensive manual methods based on outstanding job lists in AMPS. Each MSD SPO develops such work lists using locally developed procedures without the benefit of tools to provide commonality of approach, and the objective and auditable optimisation of work lists. To improve cost effectiveness and efficiencies in this activity Directorate of Maritime Sustainment Support (DMARSS) proposes the integration of the MAIT and MVT packages. The MVT is an adaptation of the mean variance portfolio theory used routinely within the finance sector. With relatively modest data requirements the technique allows the identification of 'efficient frontier' solutions (for example in this case the combinations of maintenance activities) which provide the maximal capability return for a given level of financial risk. Hence, maintenance planning decisions can be made based on the risk-return profile required. The figure below shows the MVT logical data model. The only mandatory input data required by MVT are; a brief description of the maintenance activity, an upper and lower cost for each activity, the list of missions the platform is to undertake in the near future and the relative importance of each mission, and an importance ranking (low/medium/high) of each activity to each mission. Other MVT data inputs are optional and basically provide for easy comparison of activity options. Achievement of smart maintenance using the MAIT and MVT tools involves; • using MAIT to compile the complete outstanding maintenance work list from AMPS and export that work list and other relevant data into a format readable by the MVT; • using MVT to develop an efficient "optimised" solution of maintenance activities based on budgetary and other constraints from either the complete outstanding work list, or CMC sub-groupings of the outstanding work list; • returning the optimised work list to MAIT in order to produce an endorsed work list for contract tendering and update the AMPS outstanding work list; • using MVT to compare tender responses in the event that responses differ from the endorsed work list, and return that final data pack to AMPS through MAIT. Advantages of the mean-variance approach as an aid to maintenance and configuration management decision making are as follows: • Data entry is modest. • Selection of work package options from the efficient frontier lowers the risk in funding a set of sub-optimal work package options. • Ability to maximise overall platform capability for a given level of funds. • Ability to minimise costs for a given level of overall platform capability. • The software and data entered can be shared, hence making the underlying assumptions visible to a group leading to group agreement/ consensus on ranking and cost variability data. • The software provides a robust, repeatable and auditable process for work package prioritisation. The smart maintenance approach using the combination of enhanced MAIT and MVT features described above, will initially be tested as part of SPO business in the AAS SPO and ANZAC SPO, prior to general deployment to MSD SPOs. Upon being proven in practice in the maintenance domain, the smart maintenance approach could be further enhanced to form the basis of a smart materiel sustainment method. In this approach, configuration management changes (including upgrades/updates) and maintenance could be combined and assessed as a whole to provide optimised work activities for availabilities of each platform. Furthermore, with modification, MAIT/MVT Smart Maintenance Initiative from DGMARSPT In the last issue readers were introduced to two leading edge software tools developed by DSTO under the sponsorship of DGMARSPT. BY MS HALINA SCOTT