2016 Maintenance Innovation Challenge

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Presentation transcript:

2016 Maintenance Innovation Challenge Implementation of CBM+ to Enable Data Driven Fleet Management PROBLEM STATEMENT Studies have determined that operations and sustainment costs for military ground vehicles represent 68% of the total life cycle cost. The Army has advocated that CBM+ can decrease O&S costs. TACOM ILSC and AMSAA are working to validate this concept. In addition, an Office of the Auditor General - Army, audit of ground operating tempo determined that there is a 51% understatement of the actual vehicle mileage for FORSCOM units. The study indicated that ‘Inaccurate mileage hinders DA’s ability to determine an accurate OPTEMPO posture, develop an accurate budget, and perform overall fleet management and maintenance.’ BENEFITS The implementation of CBM+ using vehicle sensor data improves the maintenance capability and fleet management benefits for the U.S. Army TWV fleet. DASA-CE reviewed monetary savings will be seen in the following areas: 43% are derived from lubrication savings, 28% from overhaul savings, 19% from parts savings and 10% are derived from fuel associated cost avoidances or cost savings. The CBA shows a benefit of CBM+ implemented on 1740 vehicles with a net savings of $45M over 20 years, TACOMs Sensitivity Analysis shows a $1.2B net savings on 58,996 vehicles over 20 years. TECHNOLOGY SOLUTION This TACOM ILSC and AMSAA Program executed the CBM+ Sustainment Implementation Guide that was developed by the U.S. Army Deputy Chief of Staff, G-4. Vehicles instrumented with low cost digital source collectors enables automated CBM+ data (i.e. vehicle usage, fault code and parametric sensor data) collection. Data analysis processes provide the ability to create actionable information to enable data driven maintenance and sustainment decision making for fleet management: Usage Based Oil Change Interval Vehicle RESET selection based on vehicle sensor data Enabling predictive analytics for component failure GRAPHIC Usage Data Dashboard Analysis Engine Automated Reports