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

Cornell University Operations Research and Industrial Engineering

Cornell University Operations Research and Industrial Engineering NASA Goals

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

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

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

Cornell University Operations Research and Industrial Engineering Time Maintenance cycle starts for successive vehicles Scheduled maintenance cycle completions RLV Maintenance Cycles

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

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

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

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

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

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

Cornell University Operations Research and Industrial Engineering 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 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 Identify Events

Cornell University Operations Research and Industrial Engineering Model Delay Between Events

Manage Priorities

Track Inventories

Cornell University Operations Research and Industrial Engineering Select Inputs

Cornell University Operations Research and Industrial Engineering Capture Outputs

Cornell University Operations Research and Industrial Engineering Sample Cases Case 1: Ample Capacity Case 2: Sufficient Inventories Case 3: Effective Service Priorities Three Cases using Simulator RLV arrivalsevery 50 days RLV ground time20 days LRU work stations5 SRU work stations5 Service times days Repair priority rulesimple Baseline:

Cornell University Operations Research and Industrial Engineering Case 1: Ample Capacity Baseline Case Results Percent of RLVs Delayed: Average Delay Time: Case 2: Sufficient LRU Inventories Percent of RLVs Delayed: Average Delay Time: Case 3: Effective Repair Priorities Percent of RLVs Delayed: Average Delay Time: Sample Cases Simulation Results

Cornell University Operations Research and Industrial Engineering 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