Logistics Information Systems for Human Space Exploration: State of the Art and Emerging Technologie

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Logistics Information Systems for Human Space
Exploration State of the Art and Emerging
TechnologiesSarah A. Shull (sshull_at_mit.edu)Eric
a Gralla, Matthew Silver, Prof. Olivier de Weck
Massachusetts Institute of Technology SpaceOps
2006 Rome, ItalyJune 21, 2006
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Overview of Presentation

• Current Practices in Space Logistics
• Lessons Learned from Past/Current Programs
• Emerging Technologies
• RFID
• SAW
• Integrated Modeling
• Relational Database
• SpaceNet
• Conclusions

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Current Practices ISS

• Procurement, manifesting, parts catalog.all
  separate databases
• Inventory Management System is single source for
  on-orbit inventory tracking
• Until recently EVA and CHeCS also tracked their
  H/W on-orbit
• Most items on ISS are barcoded
• Locations are also barcoded
• Most stowage is in the U.S. Node and Russian FGB
• Conditional stowage locations include Joint
  Airlock, PMA1, PMA2, PMA3, Z1 Pressure Dome, DC-1
• Where possible stowage on ISS is functionally
  grouped
• Medical (CHeCS) Rack
• PMA1 for Bags of Clothing, Towels
• Food Containers on Node Deck

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IMS Overview

• The Inventory Management System (IMS) is the
  database used on the ISS and by the flight
  control team for inventory management.
• Jointly developed by NASA and RSA
• The DB is SQL Server 2000
• The GUI Software itself is written in Java
• 20,000 Items currently tracked in IMS
• Of this the items lost typically hovers around
  3 For the 8000 U.S. Items tracked, this means
  240 are lost
• Interfaces to hand-held barcode reader
• Can be updated by ISS Crew, Inventory and Stowage
  Officer (ISO) in Houston, Russian Inventory and
  Stowage Specialist (RISS) in Moscow or at
  Baikonur
• Crew allotted 20 minutes of IMS File Prep
  daily, in reality daily updates take much longer

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Lessons Learned from Past Programs

• Joint study with colleagues at United Space
  Alliance
• Searched crew debriefs, the John Commonsense
  lessons repository for the Mission Operations
  Directorate, Lessons Learned from Phase 1/MIR and
  the Johnson Space Center (JSC) and Marshall Space
  Flight Center (MSFC) Skylab Lessons Learned
• Distilled to Top 7 Lessons Learned, 4 of which
  are very relevant to todays talk
• There should be design influence or specification
  to provide for stowage volume.
• The inventory system should be based on a common
  logistics system, shared by multiple
  organizations, to decrease the problem of
  differing values for like items across systems.
• Packing lists and manifests do not make good
  manual accounting systems. Parent-child
  relationships are fluid and need to be
  intuitively handled by a system updated by the
  movement of both parents and children.
• Include return logistics requirements in the
  design specification. Understand and model
  packaging requirements, pressurization, and
  reparability/disposability for the return or
  destructive re-entry of items ahead of time.

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One Picture 1000 Words
Wheres that hammer?

• Picture from http//spaceflight.nasa.gov/gallery/i
  ndex.html

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Emerging Technologies RFID

• Radio Frequency Identification (RFID)
• RFID is a generic term for technologies that use
  radio waves to automatically identify objects
• RFID tags are small devices containing a chip and
  an antenna that store the information for object
  identification
• RFID does not require line-of-sight

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Emerging Technologies SAW

• Surface Acoustic Wave (SAW)
• Similar to RFID
• Converts radio waves emitted by a reader into
  nano-scale surface acoustic waves on the SAW RFID
  tag
• SAW tags can operate when receiving only a
  fraction of a microwatt from the reader
• RFSAW claims that their tags can operate at
  temperatures between -100 to 200 degC

Figure from http//www.rfsaw.com/pdfs/SAW20RFID
20Whitepaper.pdf
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The Future of Asset Management
LN
Local Node
Applications
R
RFID/SAW Reader
R
RFID/SAW Tag
Real-Time Data Capture Platform
Integrate real-time RFID/SAW Barcode GPS
Interplanetary Network Connection
Internet
TDRSS
Planetary Surface
In-Space
Earth Ground
LN
LN
LN
Launch vehicle
Spaceport
R
R
R
R
R
R
ISS
Lunar
CEV
Mars
Ground Processing
Base
R
R
R
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Integrated Modeling

• Modeling exploration from a logistics perspective
• Discrete event simulation
• Evaluation of manually generated exploration
  scenarios with respect to measures of
  effectiveness and feasibility
• Visualization of the flow of elements and supply
  items through the interplanetary supply chain
• Optimization of scenarios according to selected
  MOEs
• Provide software tool for users ( logisticians,
  mission architects) to support trade studies and
  architecture analyses.

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Relational Database

• Database
• Stores libraries of spacecraft, nodes, supplies
• Extensive data for demand models
• Enables real-time tracking of individual items

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SpaceNet Users and Goals

• Diverse user base
• Mission/system architects
• Mission planners and logisticians
• Operations personnel
• Etc
• Support short and long-term architecture and
  operational decisions
• What effect will vehicle (element) design
  decisions have on future NASA operations and
  lifecycle costs?
• Should a staging area or depot be constructed? In
  LEO? At LOP?
• Are in-space refueling and ISRU helpful in
  improving performance?
• Is it better to have cargo vehicles that carry
  small re-supply loads or a few large pre-deploy
  or resupply flights?

Staging Location
In-Space Refueling
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SpaceNet Concept

• Model missions on a network of nodes and arcs
• Key advantage demand-driven

Demand 4 Crew Science Eqp. Consumables Propellant
Earth
LEO
LLO
Moon
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SpaceNet
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Scenarios

• With SpaceNet, we have modeled
• Single sortie missions
• Constellation sortie
• Apollo 17
• LEO refueling in Constellation
• ISRU on lunar surface
• Entire campaigns
• Constellation lunar base build-up
• ISS assembly and re-supply

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Conclusions

• Current logistics system will not be sufficient
  for lunar and Mars missions
• Lessons learned from past and current programs
  highlight the need to consider logistics early in
  the design process
• Emerging technologies such as RFID and SAW show
  great promise for nearly autonomous asset
  management
• The capability to do integrated modeling is
  critical early in the design process
• SpaceNet offers that capability
• With SpaceNet we have modeled single sortie
  missions and campaigns and performed trade studies

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Questions?