Readiness Based Customer- Wait -Time Sparing within a Commercial Advanced Planning System

1. CELDi Center for Engineering Logistics & Distribution Readiness Based Customer- Wait -Time Sparing within a Commercial Advanced Planning System Principal Investigator: Manuel D. Rossetti, Ph.D., P.E. Co-Principal Investigator: Erhan Kutanoglu, Ph.D. CELDi Research Assistant: Nancy Sloan, M.S.O.R. Graduate Research Assistant: Ashish Achlerkar

2. CELDi Center for Engineering Logistics & Distribution Description To determine the potential for improving supply support throughout the Navy and Air Force, with a focus on integrating wholesale and retail inventory models to achieve readiness based customer wait time (CWT) goals.

3. CELDi Center for Engineering Logistics & Distribution Objectives • Evaluate an inventory model that can develop CWT spares budgets for the Navy and Air Force. • Examine a common integrated spares model for the Navy and Air Force that can be implemented in a commercial Advanced Planning System (APS). • Reduce total inventory investment necessary across the Navy and Air Force while achieving comparable or better performance and meeting the high logistics system performance standards of the Navy and Air Force.

4. CELDi Center for Engineering Logistics & Distribution Experimental Plan • Assess COTS X sparing solution for the FA-18 data set, comparing and contrasting solution with results of an early study using COTS Y and the Navy’s ARROWs. • Assess COTS Y as a potential bridge for the gap between wholesale and retail stocking policies. Evaluate the realignment of these two into a possible solution. • Assess the feasibility of using Center for Naval Analysis’ (CNA) shortage cost methodology. • Explore and assess inventory segmentation strategies and clustering algorithms.

5. CELDi Center for Engineering Logistics & Distribution Background • Complex inventory decisions for repair parts • multi-echelon system, multi-indenture parts • Readiness based sparing decisions for US military • Readiness: the ability of US military forces to fight and meet the demands of the national military strategy. • Goals: Maximize equipment availability (Ao) Minimize customer wait time

6. CELDi Center for Engineering Logistics & Distribution Inventory Theory • Vari-metric models • Spare parts optimization • Multi-echelon multi-indenture models • Segmentation • CWT • Shortage Cost • Theorists: • Sherbrooke [‘92] • Cohen [‘86- - ‘03] • Zipkin [‘88, 00] • Svoronos [‘88] • Slay et al. [‘96] • Nickel et al. [‘01]

7. CELDi Center for Engineering Logistics & Distribution Tools • Company X • COTS software • “Push” type model • Forecast based • Company Y • COTS software • Retail + wholesale stocking decisions • “Pull” type model • Company Z • COTS software • Service parts optimization • Forecast based • Lost sales model

8. CELDi Ao R Q Center for Engineering Logistics & Distribution Tests • F/A-18 Parts Set • Consumables and Repairables • 4671 Parts at 3 Indentures • Find the R’s and Q’s that give the best Ao

9. CELDi Center for Engineering Logistics & Distribution Test Results

10. Technical and Costs ‘true’ BEST (green) ‘Ideal’ BEST (blue) CELDi Quantitative Worst (red) Center for Engineering Logistics & Distribution Qualitative Evaluation • Criteria • Quantitative • Qualitative • Technical and Costs • Rating • Risk Analysis

11. CELDi Center for Engineering Logistics & Distribution Outcomes • Less risk to continue with 2 competitors for SMART 2.5

12. Cdr. Leigh Ackart Systems integrator CELDi Center for Engineering Logistics & Distribution CELDi researchers The Team