Quantifying the Effect of Commercial Transportation Practices in Military Supply Chains

1. CELDi Center for Engineering Logistics & Distribution Quantifying the Effect of Commercial Transportation Practices in Military Supply Chains Research Program Review ASC PA 03-2417 9/15/03

2. Researchers Manuel D. Rossetti, Ph. D., P.E. Associate Professor Department of Industrial Engineering University of Arkansas . Scott J. Mason, Ph. D., P.E. Assistant Professor Department of Industrial Engineering University of Arkansas

3. Research Team

4. Project Description • Identify applicable successful commercial transportation practices such as direct shipments, lateral shipments, scheduled deliveries, express deliveries, etc. • To quantify the effects commercial transportation practices on military supply chains • Primarily examining the depot/base repair, inventory, and transportation processes for unscheduled maintenance actions for multi-indentured weapon systems • Expected Deliverables: • Strategic policy recommendations concerning which commercial practices to adopt to improve aircraft availability and reduce cost • Simulation model(s) of examined processes • Project report

5. Project Progress *** Completed *** Scheduled A = Progress report due B = Model walk-through C = Draft model documentation D = Presentation of results E = Final report completed

6. Supply Chain Scenario Development (Fall 2002) • Identified and defined commercial transportation practices that are applicable to military supply chains • Identified successful transportation practices that have had success in other branches of the military • Practices include: • Lateral Shipping • Scheduled Deliveries • Direct Shipments • Express Air Carriers • Conceptualized military supply chain as a multi-indenture, multi-echelon (MIME) spare parts inventory system

7. aircraft2 aircraft1 aircraft3 Base2 aircraft1 aircraft1 Base3 aircraft2 Base1 aircraft2 Depot aircraft3 aircraft3 Repaired part Repair Facility Inventory Warehouse Failed part Spare part Airaircrafts Supply Chain Scenario Development An example MIME system with one central depot serving three bases which in turn operate several weapon systems– in this case aircraft The failure and repair cycle for an aircraft part

8. Identifying Performance Metrics (Fall 2002) • Identified and defined performance metrics that accurately reflect the goals of the Air Force’s repairable parts inventory system • Metrics include performance metrics and resource (cost) metrics • These metrics will be used to compare different transportation scenarios • Developed methods to compute these metrics within the simulation models

9. Identifying Performance Metrics Metrics include: • Mission Capability (MC) - high-level metric • Customer Wait Time (CWT) - time from when an order is placed to when the spare part arrives • Fill Rate - percentage of requests that are filled immediately • Accommodation Rate - percentage of requests that are for items that are regularly stocked (measures inventory breadth) • Satisfaction Rate - percentage of requests for regularly stocked parts that are filled at that time (measures inventory depth) • Inventory Cost - cost associated with maintaining a certain inventory size • Transportation Cost - cost associated with transporting parts between bases and depots

10. Literature Review (Fall 2002 - Spring 2003) • Topics covered: • Relevant metrics • Cross-docking • Private Express Carriers • Scheduled Deliveries • Direct Shipments • Lateral Shipments • Scheduling at the Repair Shop • Cannibalization • Part Failures • 28 pieces of literature reviewed

11. Literature Review Highlights (Fall 2002 - Spring 2003) • Reducing ordering and shipping times has a greater impact on MC than improving the inventory of spares (Kang et. al. 1998, Ramey 1999) • Using next-day and two-day deliveries achieves the same MC with only 1/6th of the current inventory levels (Ramey 1999) • Implementing scheduled deliveries has improved the Army’s median, 75th, and 95th percentile CWT by 56-59% (Dumond 2001) • Reliable scheduled deliveries can drastically decrease the variance in CWT (Wang and Champy 2000)

12. Simulation Model Development (Fall 2002 - Summer 2003) • Baseline simulation model built in Arena 7.0 • Baseline model serves as a standard for comparison to alternative shipping scenarios • Modeling topics: • Weapon Systems and Bases • Failures • Sorties • Pre/Post Flight Inspection • Inventories at the Base and Depot Level • Installation Process at the Base Level • Repair Process • Shipping

13. Current Simulation Model

14. Current Simulation Model Submodel: Constituent modules: • Each submodel is comprised of individual modules • Objects (e.g. aircrafts, spare parts, and shipping trucks) flow through these modules • Each submodel simulates a specific portion of the failure and repair process

15. Modeling Weapons Systems and Bases • Aircraft are modeled as objects • Assigned index, aircraft, and base numbers • Base number indicates the base at which the aircraft is stationed • Aircraft have two levels of indenture: LRUs and SRUs • Each aircraft is comprised of multiple LRUs and each LRU comprised of multiple SRUs • Each aircraft is comprised of the same LRU types and each LRU type is comprised of the same SRU types • Failure of one SRU results in failure of the whole LRU and failure of one LRU results in failure of the aircraft

16. Modeling Failures • Failures are based on flight hours • Each SRU of each aircraft is initially assigned a time-to-failure (TTF) value • Failure occurs when one SRU exceeds the TTF • TTF are decreased as the aircraft flies sorties • When any value in this matrix becomes less than or equal to zero, the SRU corresponding to that cell in the matrix has “failed”

17. Modeling Sorties • Sorties are created at the beginning of each day and assigned to each base • The number and duration of sorties is assigned by randomly generated numbers • Sorties wait until a aircraft from that base flies them • When a aircraft is assigned a sortie, it is delayed the duration of that sortie • After the sortie is flown, each value in the aircraft’s TTF matrix is decremented by the duration of the last sortie flown • Unflown sorties are cancelled at the end of each day

18. Generating Sorties • Assigned sorties waiting for aircraft • Aircraft waiting for assigned sorties

19. Modeling Pre/Post-Flight Inspections • After subtracting the sortie duration from each cell, the model checks if any of the values of the aircraft’s TTF matrix are less than zero • If not, the aircraft is released to fly another sortie • If so, the aircraft is in failure and begins to wait for a spare part • Once a spare part becomes available at the aircraft’s base, the aircraft is released to begin installation of that spare part

20. Mission Capability Metric • Current status of a aircraft is 1 when it is functional and 0 when it has failed • Aircraft’s current status is set to zero when it begins to wait in queue for a part • Mission Capability (A0) is the time-persistent average of the aircraft’s current status

21. Modeling Inventories and Locating Spares • Once an aircraft is determined to be in failure, the model checks to see if a spare part is first available in the aircraft’s base inventory and then the depot inventory • Inventory at the bases and depots is treated as two-dimensional arrays • The numbers in the arrays represent the number of spare parts of that type available at that location • If the base has the necessary spare part, the order is filled by the base; if not, the model sends the order to be filled by the depot • Once a spare is made available at the base, the order releases the spare and the aircraft to enter the installation process

22. Modeling the Installation Process • Once the spare part is available at the base, the aircraft enters the installation process • Upon entering the installation process, the cell corresponding to the spare part is decremented by one • A finite resource is used to install the spare part on the aircraft • Upon completion of the installation, the aircraft is released to fly sorties

23. Modeling the Repair Process • Based on a discrete random probability, failed parts are either sent to the depot or kept at the base for repair • If the part is sent to the depot, an order is also sent to replenish that part in the base’s inventory • If the part is kept at the base, the part is repaired, and restocked in the base’s inventory, incrementing the corresponding value in the base’s inventory matrix • Repair at both levels is done using a finite resource

24. Modeling Shipping • Current model ships spare parts between the depot and bases using a finite number of trucks • Trucks wait until enough parts are ready for shipment (either at a base or the depot) • Truck capacity is limited by a user-set maximum number of SRUs • Travel time to bases varies, simulating geographic differences in bases • Shipping scenarios will be further discussed in “Experimentation”

25. Verification, Validation, and Testing (Summer 2003) • Model assumptions consistent with the assumptions made by RAND’s DRIVE Model • Model tracks metrics including: • Average MC for each aircraft and for the entire fleet • Average CWT per aircraft and system-wide • Total number of failures per aircraft • Total number of sorties flown per aircraft • 06/12/2003 - Presented model walk-through to AFRL and military contacts and received feedback on the accuracy of the simulation • Presently working to implement the feedback received

26. Experimentation (Summer 2003 - Fall 2003) • Developing hypothetical shipping scenarios for future comparison • Current models simulate direct shipments: Trucks travel only to and from the depot; never between bases • Future models will simulate: • Routes - trucks leave depot and travel to several bases before returning to the depot • Lateral shipments - bases receive spare parts from the depot as well as other bases • Expedited air shipments - MICAP parts are shipped using expedited air shipments, while other parts are transported using trucks

27. Analysis of Results (Fall 2003) Will compare developed hypothetical shipping scenarios based on the aforementioned metrics: • MC rate • CWT • Fill Rate • Inventory Cost • Transportation Cost

28. Model Documentation (Spring 2003 - Fall 2003) • Submitted a draft document, including the literature review and simulation model description, to AFRL and military contacts in May 2003 • Suggestions and feedback on this document are being incorporated into a new draft • Simulation model description is being expanded to include all developed shipping scenarios

29. Final Report (Spring 2003 - Fall 2003) • Initial drafts of this document are already in progress • Final report will present data on the aforementioned metrics across the various shipping scenarios • Will present strategic policy recommendations concerning which commercial practices to adopt to improve aircraft availability and reduce cost

30. Questions?