Simulating Ground Support Capability for NASA’s Reusable Launch Vehicle Program

1. Simulating Ground Support Capability for NASA’s Reusable Launch Vehicle Program Kathryn E. Caggiano Peter L. Jackson John A. Muckstadt Cornell University Operations Research and Industrial Engineering

2. Cornell University Operations Research and Industrial Engineering

3. NASA Goals Cornell University Operations Research and Industrial Engineering

4. Reusable Launch Vehicle Program Today: Space Shuttle 1st Generation RLV • Orbital Scientific Platform • Satellite Retrieval and Repair • Satellite Deployment 2010: 2nd Generation RLV • Space Transportation • Rendezvous, Docking, Crew Transfer • Other on-orbit operations • ISS Orbital Scientific Platform • 10x Cheaper • 100x Safer 2025: 3rd Generation RLV • New Markets Enabled • Multiple Platforms / Destinations • 100x Cheaper • 10,000x Safer 2040: 4th Generation RLV • Routine Passenger Space Travel • 1,000x Cheaper • 20,000x Safer Cornell University Operations Research and Industrial Engineering

5. Intact Abort Safety Crew Escape Reduced Variability Design Cycle Development Cost Fleet Production Design for Manufacturing Simplify Design Minimize Part Count Systems Approach: Safety, Reliability, and Cost Weight Margin Inherent Reliability Robust Design Operating Margin Redundancy IVHM 10,000x Safer Toxic Fluid Operations Move Operating Range/De-rate Add Material Capability/Weight 100x Cheaper Interfaces Accessibility Range Operations Requires Increased Margin Reduce Variability Cornell University Operations Research and Industrial Engineering Requires Increased Testing

6. Marshall Space Flight Center: NASA Flight Projects Directorate • Project Management • Systems Engineering & Integration • Payload Operations Engineering & Integration • Mission Preparation & Execution • Mission Training Requirements & Processes • Ground System Design, Development, and Test • Facility Operations Cornell University Operations Research and Industrial Engineering

7. Cornell Project Goals Develop analysis tools for determining and evaluating spare parts stocking policies for avionics components of Reusable Launch Vehicles Cornell University Operations Research and Industrial Engineering

8. Project Objectives Construct a methodology that: • Evaluates the effectiveness of a proposed logistics support strategy • Determines stock levels for recoverable items needed to operate the system effectively Cornell University Operations Research and Industrial Engineering

9. System Framework • RLV Ground Maintenance Process • Line Replaceable Unit (LRU) Repair Process • Shop Replaceable Unit (SRU) Repair Process Cornell University Operations Research and Industrial Engineering

10. Vehicle Launches In-Flight Time Pre-Launch Activities Commence Vehicle Returns Planned Maintenance Cycle RLV Mission Cycle Cornell University Operations Research and Industrial Engineering

11.  Scheduled maintenance cycle completions Maintenance cycle starts for successive vehicles 0  2 3 3 +    Time RLV Maintenance Cycles Cornell University Operations Research and Industrial Engineering

12.  Maintenance Cycle Begins Maintenance Cycle Scheduled to End LRUs tested for soundness One Maintenance Cycle Failed LRUs must be replaced by the scheduled end date in order to avoid a delay. Cornell University Operations Research and Industrial Engineering

13. RLV Begins Service RLV Ends Service LRU Inventory RLV Ground Maintenance Test LRUs Remove and Replace Failed LRUs Cornell University Operations Research and Industrial Engineering

14. SRU Inventory Test LRUs RLV Begins Service Remove and Replace Failed LRUs Diagnose LRU Failure Remove and Replace Failed SRUs RLV Ends Service LRU Inventory Repair LRU LRU Repair Process Cornell University Operations Research and Industrial Engineering

15. SRU Inventory Test LRUs RLV Begins Service Remove and Replace Failed LRUs Diagnose LRU Failure Remove and Replace Failed SRUs Repair SRU RLV Ends Service LRU Inventory Repair LRU SRU Repair Process Cornell University Operations Research and Industrial Engineering

16. RLV Begins Service RLV Ends Service System Framework SRU Inventory Test LRU Remove and Replace Failed LRU Diagnose LRU Failure Remove and Replace Failed SRUs Repair SRU LRU Inventory Repair LRU Cornell University Operations Research and Industrial Engineering

17. Repair Facility Location Transport Method Product Design Repair Technology Repair Capacity Priority Rules SRU Repair Cycle Time SRU Spare Inventory Levels Transport Queue Diagnosis Repair Transport Wait for SRU Failed SRU removed from LRU LRUavailable for use LRU Repair Cycle Time Failed LRUremoved from RLV Cornell University Operations Research and Industrial Engineering

18. Simulation Model Features • Captures many aspects of integrated system • Outsourcing and condemnation • Limited capacity for in-house diagnosis and repair • Probabilistic transport and service times • Limited inventories of LRUs and SRUs • Dynamic priorities • Implemented in MS Excel with VBA Cornell University Operations Research and Industrial Engineering

19. A Model of RLV Repairs • Identify Events • Model Delays Between Events • Manage Priorities • Track Inventories • Select Inputs • Capture Outputs Cornell University Operations Research and Industrial Engineering

20. Identify Events Cornell University Operations Research and Industrial Engineering

21. Model Delay Between Events Cornell University Operations Research and Industrial Engineering

22. Manage Priorities

23. Track Inventories

24. Select Inputs Cornell University Operations Research and Industrial Engineering

25. Capture Outputs Cornell University Operations Research and Industrial Engineering

26. Sample Cases Case 1: Ample Capacity Case 2: Sufficient Inventories Case 3: Effective Service Priorities Three Cases using Simulator Baseline: RLV arrivals every 50 days RLV ground time 20 days LRU work stations 5 SRU work stations 5 Service times 75 - 100 days Repair priority rule simple Cornell University Operations Research and Industrial Engineering

27. Sample Cases Case 1: Ample Capacity BaselineCase Results • Percent of RLV’s Delayed: 60 46 • Average Delay Time: 41 26 Case 2: Sufficient LRU Inventories • Percent of RLV’s Delayed: 60 27 • Average Delay Time: 41 39 Case 3: Effective Repair Priorities • Percent of RLV’s Delayed: 60 39 • Average Delay Time: 41 25 Simulation Results Cornell University Operations Research and Industrial Engineering

28. Sample Cases 1. Sufficient service capacity significantly improves on-time performance. 2. Appropriate LRU and SRU inventory levels improve performance considerably. 3. Effective repair priorities increase utilization, reduce costs, and improve on-time performance. 4. System utilization rates, inventory levels, and on-time service targets cannot be selected independently. Four General Lessons Cornell University Operations Research and Industrial Engineering