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ESD.71 – Engineering System Analysis for Design December 9, 2008 Abe Grindle

Valuing Flexibility in the Face of Uncertainty: Deploying RFID-wired Cargo Bags on the International Space Station, 2009-2016. ESD.71 – Engineering System Analysis for Design December 9, 2008 Abe Grindle. Aurora Flight Sciences / Payload Systems Division. Outline. Background & Motivation

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ESD.71 – Engineering System Analysis for Design December 9, 2008 Abe Grindle

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  1. Valuing Flexibility in the Face of Uncertainty:Deploying RFID-wired Cargo Bags on the International Space Station, 2009-2016 ESD.71 – Engineering System Analysis for Design December 9, 2008 Abe Grindle Aurora Flight Sciences / Payload Systems Division

  2. Outline • Background & Motivation • Previous Work • Current Objectives • System Description & Definitions • Assumptions • Decision Tree Analysis • Lattice Analysis • Conclusions

  3. Background: ISS Inventory Architecture • Barcodes + manual barcode scanner • CTBs (Cargo Transfer Bags) and other bags/kits • 1/2, Standard, Double, Triple • Concentration of Inventory Transactions • IMS (Inventory Management System) • Software database of all inventory information • Copies in Houston, Moscow, Baikanour, and ISS • Delta files • Proposed: RFID Systems in CTBs • Antennas, Readers, Battery & Wi-Fi in CTBs • Gen II passive RFID tags on all items Aurora Flight Sciences / Payload Systems Division

  4. Motivation: Automate the ISS Inventory Process @ ISS Assembly Complete: • 600 Cargo Transfer Bags (CTBs) on-orbit • 730 Crew Hours / Year spent updating IMS ~ 4 ½ person-months (40 hrs/wk) Questions: • Could we save some of this time with a CTB-based RFID inventory system? • Would this provide net value? Image Credits: NASA / Rule-Based Analytic Asset Management for Space Exploration Systems (RAMSES) STTR Phase I Final Report (de Weck, et al. 2007) Aurora Flight Sciences / Payload Systems Division

  5. Previous Work • January 2008 • Study of ISS Logistics & Inventory Processes • Spring 2008 • Development of Cost Model to evaluate Expected Net Present Value (ENPV) of RAMSES RFID System • Hardware Prototype development • Analysis of ENPV given hardware & performance uncertainties (single v. inflexible phased deployment) Aurora Flight Sciences / Payload Systems Division

  6. Objective of this Study • Evaluate: RFID deployment strategies in the context of uncertain demand, system performance, and lifetime. • Fixed deployment: • all RFID systems launched in 2009 • Flexible: • Some RFID systems launched in 2009 • Option to launch additional systems in 2012 Aurora Flight Sciences / Payload Systems Division

  7. System Description & Definitions CTB Deployed RFID Systems = “Wired” CTBs Inventory Transactions = “Demand” “Captured” Demand Aurora Flight Sciences / Payload Systems Division

  8. Concentration of Demand Uniform Demand 25% RFID Deployment captures 25% (2/8) of “Demand” 25% RFID Deployment captures 37.5% (3/8) of “Demand” 25% RFID Deployment captures 50% (4/8) of “Demand”

  9. Assumptions • Initial deployment of RFID systems occur in 2009 • Benefits do not begin to accrue until 1 year after decision to deploy • ISS will have crew of 6 at start of 2010 • “Planned” ISS retirement (for US) in 2016 Aurora Flight Sciences / Payload Systems Division

  10. Decision Tree Analysis • Fixed Strategy: • 2009 RFID Deployment = 33.3%of ISS CTBs • Flexible (Incremental) Strategy: • 2009 RFID Deployment = 16.7% of ISS CTBs • 2012 Option = +16.7%(for total of 33.3% of ISS CTBs) • 2 Elements of Uncertainty (Chance Nodes): • Is there Concentration of Demand? • When will the ISS actually be retired? Aurora Flight Sciences / Payload Systems Division

  11. EPV = $(21.16) M EOL = 2020 Est. Prob. = 0.1 C EOL = 2018 EPV = $(26.78) M ISS End Of Life (EOL) = 2020 EOL = 2016 EPV = $(33.22) M EOL = 2018 Expand Deployment (to 33.3%) Est. Prob. = 0.2 EOL = 2014 EPV = $(40.59) M EPV = $(31.46) M D EOL = 2016 Est. Prob. = 0.6 EPV = $(11.71) M EOL = 2020 EOL = 2018 C EPV = $(14.32) M EOL = 2014 Maintain 16.7% Deployment Est. Prob. = 0.1 EOL = 2016 EPV = $(17.32) M EPV = $(16.50) M EOL = 2014 EPV = $(20.74) M 8.33% Demand Captured Est. Prob. = 0.1 EPV = $16.68 M EOL = 2020 Flexible Delayed Deployment Strategy (100 CTBs ~ 16.7%) EOL = 2018 C EPV = $5.04 M EOL = 2016 EPV = $(8.28) M Expand Deployment (to 33.3%) EOL = 2014 EPV = $(23.54) M EPV = $(4.65) M 16.7% Demand Captured D C EPV = $11.22 M EOL = 2020 Est. Prob. = 0.3 EOL = 2018 C EPV = $5.60 M EPV = $11.93 M Maintain 16.7% Deployment EOL = 2016 EPV = $(0.83) M EPV = $0.92 M EOL = 2014 EPV = $(8.20) M 25% Demand Captured Est. Prob. = 0.6 D EPV = $54.51 M EOL = 2020 EOL = 2018 C EPV = $36.86 M Expand Deployment (to 33.3%) EOL = 2016 D EPV = $16.65 M EPV = $22.17 M EOL = 2014 EPV = $(6.48) M Fixed Up-Front Deployment Strategy (200 CTBs ~ 33.3%) EPV = $34.15 M EOL = 2020 Maintain 16.7% Deployment EOL = 2018 C EPV = $25.52 M EPV = $18.34 M EOL = 2016 EPV = $15.65 M EOL = 2014 EPV = $4.33 M EPV = $12.30 M EPV = $(18.62) M EOL = 2020 Maintain 33.3% Deployment EOL = 2018 D C EPV = $(24.24) M 16.7% Demand Captured EOL = 2016 EPV = $(30.68) M EPV = $(28.92) M EOL = 2014 Est. Prob. = 0.1 EPV = $(38.04) M C 33.3% Demand Captured EPV = $27.24 M EOL = 2020 Maintain 33.3% Deployment D C EOL = 2018 Est. Prob. = 0.3 EPV = $15.61 M EOL = 2016 EPV = $5.92 M EPV = $2.29 M EOL = 2014 EPV = $(12.97) M 50% Demand Captured Est. Prob. = 0.6 EPV = $73.11 M EOL = 2020 Maintain 33.3% Deployment EOL = 2018 D C EPV = $55.46 M EOL = 2016 EPV = $22.36 M EPV = $35.25 M EOL = 2014 EPV = $12.11 M 2009 2012 2014-2020

  12. Decision Tree Analysis Aurora Flight Sciences / Payload Systems Division

  13. Decision Tree Analysis • Results: • Fixed Strategy has larger ENPV than Flexible, as considered here • Why? • Large Capex required (launch & installation costs) • Low recurring cost, High recurring benefits Aurora Flight Sciences / Payload Systems Division

  14. Decision Tree Analysis Aurora Flight Sciences / Payload Systems Division

  15. Lattice Analysis • Fixed Strategy: • 2009 RFID Deployment = 25%of ISS CTBs • Flexible (Incremental) Strategy: • 2009 RFID Deployment = 25% of ISS CTBs • 2012 Option = +10%(for total of 35% of ISS CTBs) • Uncertainty: • How much time will a given deployment save the crew? • Current schedule = 20 min / day / crewmember for Inventory Aurora Flight Sciences / Payload Systems Division

  16. Lattice Analysis • Growth Rate = 10% (over 6 yrs) Volatility = 20% (over 6 yrs) • Somewhat arbitrary; account for learning effects & uncertainties • Probability of Increase = ~ 60% Prob. of Decrease = ~ 40% • Upside Factor = ~ 1.09 Downside Factor = ~ 0.92 • Initial Value = 14.40 minutes • Corresponds to 25% RFID deployment, uniform distribution of transactions, crew of 6, manual inventory time of 20 min/day/crew Aurora Flight Sciences / Payload Systems Division

  17. Lattice Analysis Aurora Flight Sciences / Payload Systems Division

  18. Lattice Analysis Aurora Flight Sciences / Payload Systems Division

  19. Lattice Analysis Aurora Flight Sciences / Payload Systems Division

  20. Lattice Analysis: Dynamic Programming (not inc. Capex) 25% Fixed 35% Fixed 25% + 10% Flexible Aurora Flight Sciences / Payload Systems Division

  21. Lattice Analysis: Effects of Capex Aurora Flight Sciences / Payload Systems Division

  22. Lattice Analysis: Conclusions • Results: • Flexible strategy has slightly larger ENPV than baseline fixed deployment (25% in 2009), but only when Capex is not included. • With Capex, flexible option is a net loss in value. • Expanded initial fixed deployment (35% in 2009) is better than either. • Why? • Large Capex required (launch & installation costs) • Low recurring cost, High recurring benefits Aurora Flight Sciences / Payload Systems Division

  23. Thank you! Questions? Aurora Flight Sciences / Payload Systems Division

  24. Back-up Slides Aurora Flight Sciences / Payload Systems Division

  25. Inventory Transactions (“Demand”) are uniformly distributed between 100% of CTBs Concentration of Demand: 75% (6/8) of Transactions occur in 50% of the CTBs Concentration of Demand: 50% (4/8) of Transactions occur in 25% of the CTBs

  26. 25% of CTBs “Wired” with RFID Systems 50% of CTBs “Wired” with RFID Systems 75% of CTBs “Wired” with RFID Systems Percent (%) Deployment

  27. 25% RFID Deployment captures 25% (2/8) of “Demand” 50% RFID Deployment captures 75% (6/8) of “Demand” 75% RFID Deployment captures 87.5% (7/8) of “Demand”

  28. Costs Considered • NASA Engineer Time for: • Flight Certification & Approval • Operational Support & Maintenance • Cost for Vendor to Modify CTBs or Cost to Build Mod-Kits • Cost of RFID Hardware • “Opportunity Cost” of: • Launching the System Mass • Launching the System Volume • Crew Time to Transfer Items to Wired Bags or Install Mod Kits Aurora Flight Sciences / Payload Systems Division

  29. Benefits Considered • Value of Crew Time Saved on: • Bi-annual Inventory Audits • Missing Item Searches • Daily Inventory Management System Updates • Reduced workload for JSC Inventory Stowage Officers (ISOs) • Less need to assist Crew with Inventory updates/searches • Only Partial Savings realized, per “System Effectiveness” (β) parameter: β = (% of Inventory Transactions ‘Automate-able’) x (System Accuracy) Aurora Flight Sciences / Payload Systems Division

  30. Quantifying Value (“Opportunity Cost”) of Cargo Launch Volume & Mass • Value of Cargo Launch Volume = [Annual Net Variable Recurring Cost (all Cargo Missions)] [Annual Net Dry Cargo Launch Volume Available (habitable)] = ~ $20.3 million / m^3 (‘09-’10), ~ $31.6 million / m^3 (‘10-’16) • Value of Cargo Launch Mass = [Annual Net Variable Recurring Cost (all Cargo Missions)] [Annual Net Cargo Launch Mass Available] = ~ $25,500 / lb (‘09-’10), ~ $35,700 / lb (‘10-’16) Aurora Flight Sciences / Payload Systems Division

  31. Quantifying Value of On-Orbit Crew Time • Value of 1 Hour of On-Orbit Crew Time = [Average Annual ISS Ops Budget (Common Systems Operations Cost)] [# Crew] x [# “Active” Hours per day / Crew Member] x [365 days/yr] = ~ $185K / hr (’09) # Crew = 3, Each active 16 hrs/day = ~ $ 100K / hr (’10-’16) # Crew = 6, Each active 16 hrs/day • Notes: • Common Systems Operations (CSO) Cost is defined as “the cost to operate the ISS”, including “the cost to transport crew and common supplies” and “ground operations costs” [9] • International Partners’ negotiated shares of CSO Costs [10]: NASA = 76.6%; JAXA = 12.8%; ESA = 8.3%; CSA = 2.3% || RSA = Russian Segment & Crew Ops Costs Aurora Flight Sciences / Payload Systems Division

  32. Conclusions • If inventory transactions are concentrated in some subset of CTBs, and part or all of that subset can be targeted for RAMSES installation, this application of RAMSES is quite likely to result in positive Net Present Value. • Such concentration has been reported by JSC ISOs, but not quantified. Intuitively, it makes sense - some desk drawers get almost all the use. • Cost drivers:System Volume, Mass, & Crew Time required to install. • Key Benefit: Saving part of 20 min/day each Crew Member spends updating IMS (total = 730 hours/yr) . System Effectiveness (β) parameter is critical. • As with any Cost/Benefit Analysis, results are limited – can provide guidance, but not absolute truth. Assumptions and unknowns are important. Aurora Flight Sciences / Payload Systems Division

  33. Unresolved Issues / Future Work • Common Systems Operations Costs • Likely to be larger than currently calculated (baseline uses Proposed NASA FY 2009 ISS Ops Budget as reference, but this does not include launch costs)  Would increase likelihood & magnitude of NPV (increase value of Crew Time) • Russian Ops Costs unknown; likely to be larger as well? Same impact. • Dry Cargo Volume Capacity of Launch Vehicles • Only “habitable volume” is consistently available; overestimates cargo space.  Would decrease likelihood & magnitude of NPV (increase cost of cargo volume) • Benefits of Enhanced Safety and Mission Assurance are not included in this analysis • Cost of integrating RAMSES with existing IMS not included (technical & political) Aurora Flight Sciences / Payload Systems Division

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