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MICANTS

MICANTS. Vanderbilt/ISIS MIT Boeing Idea Services. Benoit Dawant Karlkim Suwanmongkol Patrick Norris Jonathan Sprinkle. Gabor Karsai Greg Nordstrom Chris vanBuskirk Jon Doyle Vera Ketelboeter George Bloor Russ Currer. MICANTS Goals. How to use Agents/Negotiation technology

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MICANTS

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  1. MICANTS Vanderbilt/ISIS MIT Boeing Idea Services Benoit Dawant Karlkim Suwanmongkol Patrick Norris Jonathan Sprinkle Gabor Karsai Greg Nordstrom Chris vanBuskirk Jon Doyle Vera Ketelboeter George Bloor Russ Currer

  2. MICANTS Goals • How to use Agents/Negotiation technology to solve complex resource management problems in (Autonomic) Logistics • To demonstrate the feasibility of the technology through real-life example(s)

  3. Roles • Vanderbilt/ISIS • MIC, implementation, and demonstration • MIT • Concepts, algorithms • Boeing • Modeling, domain knowledge • Idea Services • Domain expertise and scenarios, customer interface http://www.isis.vanderbilt.edu/Projects/micants/micants.htm

  4. Constraints Constraints BackgroundAgents/Negotiation Technology CONFLICT manages manages negotiation Mutually acceptable, Negotiated solution satisfies satisfies Objective: “Good enough solutions/soon enough”

  5. MMCO (sister squadron) MMCO options options options approve approve approve Vision: Agent-supported Maintenance Process Goal:Assistance through offering negotiated options Commander’s Intent negotiate report W/C OIC discrepancy report Assign mechanic Autonomic response negotiate Agents: • “Helpers” for the users • “Wired” to implement CO’s intent, business rules, and user guidance • Negotiate solutions autonomically • Offer options for approval negotiate Flight Schedule Shop Maintenance Schedule CAUTION: Simplified picture

  6. MAPLANT:MAintenance PLanning AgeNTs

  7. Current prototype Agents for the users • Work Center Supervisor’s Agent • Schedules calendar-based MAs • Proposes schedule(s) • Schedule displays (with options) Maintenance Control Chief’s Agent • Receives and logs gripes • Negotiates with MALS and W/C-s • Barters with sister squadron • Shows canni options • Event status display • Event/AC assignments • AC status over time • “What-if”s • Helper “agents” • Aircraft (health status) • Mission (events, flight schedule) • Jobs (maintenance actions) • Workers (maintainers) • MALS

  8. Current prototype How does it work? What can it do? • Constraint-based scheduling: • Task “start-after”s, “ends-before”-s, and durations • Task precedence • Resource constraints • Alternatives/flex assignments M/C Startup Event Status Board (M/C) • Event times • EVT/AC assignment • A/C status (OK, down, repair) • W/C Startup • Schedules calendar-based MAs • Input: • Job list with time and MOS requirements • Worker pool with qualifications • Output: • Jobs scheduled and assigned to workers • Helper startup • Aircraft (health status) • Mission (events, flight schedule) • Jobs (maintenance actions) • Workers (maintainers)

  9. Current prototype How does it work? What can it do? • MALS: • Reply with time for part availability M/C receives gripe/diagnosis • Status Board: shows conflicts • Selection: A/C + Gripe • Options: • Standard procedure (MALS) • Barter (with other M/C) • Canni (if possible) • Evaluation: • Check effects on flight schedule • Changes: • Accept/refuse proposed MA • AC to event assignment • Sister squadron M/C: • Reply with time for part availability • A/C in maintenance: • Reply with time parameters • W/C operation: • Reactive (re-)scheduling • Input: • New job with time and MOS requirements • All “old” jobs • Output: (for approval) • Multiple schedule options for new job

  10. Current prototype How does it work? What can it do? • W/C “smarts” • Rapid schedule generation • Multiple schedule options • Options are evaluated/ranked • Flexible schedule choices • Tentative scheduling choice, confirmed later M/C “smarts” • Shows/warns about conflicts with flight schedule • Keeps track of current/pending MAs • Displays available options when “repairing” AC/EVT allocations • Detects A/C in repair that can be utilized in canni • Can arrange barter with other M/C’s agent • “What-if” • Effect of the selected MA on the flight schedule • Suggests possible optimizations • Swaps (possibly with other squadron) • “Milking” • Initial data from warehouse: • Aircraft (health status) • Mission (events, flight schedule) • Jobs (maintenance actions) • Workers (maintainers)

  11. Current prototype The details • Scenario walk-through (Greg Nordstrom) • Demo (Chris vanBuskirk) WE APPRECIATE YOUR INPUT! PLEASE TELL US WHAT YOU THINK!

  12. Summary/Discussion • Agents that negotiate and offer choices to users • Scheduling, operational choices,optimization • User-driven tools • Input side: guidance • Output side: choices • In between: automatic when feasible • Plans: • Strengthening the implementation(robustness,GUI,etc.) • Refinement of functionalities (metrics, etc.) • Guidance input capability • Optimization capability (with user customization) • Cooperation with flight scheduling • Discussion: YOUR feedback

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