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Evaluation of Segmentation Techniques for Spare Parts Inventory Management: Phase 1

ACWT. Admin Lead Time (4 days). Supply Stock. AIMD 4 - 7 days. RTAT/EXREP. Resupply. Repair. BCM. (19/15 days). BCM Rate 41%. Retrograde (21 days). Wholesale Stock. $ Attrition Replenishment (12-24 Months). AWM. Depot. RTAT (45 days). Pack & Receipt (4 days).

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Evaluation of Segmentation Techniques for Spare Parts Inventory Management: Phase 1

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  1. ACWT Admin Lead Time (4 days) Supply Stock AIMD 4 - 7 days RTAT/EXREP Resupply Repair BCM (19/15 days) BCM Rate 41% Retrograde (21 days) Wholesale Stock $ Attrition Replenishment (12-24 Months) AWM Depot RTAT (45 days) Pack & Receipt (4 days) (Attrition) Evaluation of Segmentation Techniques for Spare Parts Inventory Management: Phase 1 Researcher: Manuel D. Rossetti, Ph. D., P.E. Graduate Assistant: Ashish V. Achlerkar Sponsor: Naval Systems Supply Command • Large number of spare parts to manage • High computational time and cost for policy calculations • Conventional grouping techniques do not consider operationally relevant part attributes • Need to provide differentiated service to spare parts depending upon their importance for the overall supply chain goals • Need to revise the inventory segmentation policy suggested in the NISS report in lieu of the “Readiness Based Customer-Wait Time Sparing Model Reference: Cdr.Ackart presentation slides Representative example of a Multi-echelon inventory system

  2. CELDi Center for Engineering Logistics & Distribution Research Contributions • Developed two new inventory segmentation techniques to provide an alternative to conventional inventory segmentation techniques • Developed and automated a data-generation mechanism to simulate datasets for different types of inventory systems • Evaluated different inventory segmentation techniques using experimental design • Provided general recommendations for inventory segmentation in multi-indentured, multi-echelon inventory systems

  3. CELDi Center for Engineering Logistics & Distribution Phase 2: Multi-Echelon, Multi-Indentured Spare Part Segmentation Methodologies • Expand results of phase 1 to multi-echelon setting • Investigate clustering and segmentation policies • Develop new data generation mechanisms • Develop easy to implement multi-echelon models for testing • Expand results to multi-indentured systems • Investigate mathematical formulations of clustering approaches at the same time as policy optimization

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