1. A Schedule Optimization Tool for Destructive and Non-Destructive Vehicle Tests Jeremy Ludwig, Annaka Kalton, and Robert Richards Stottler Henke Associates, Inc. Brian Bautsch, Craig Markusic, and Cyndi Jones Honda R&D Americas, Inc. ICAPS-SPARK, June 2016

2. Overview Introduction Scheduling Framework Scheduling UI Domain Customization Methods Results Deployment Conclusion

3. Introduction Create a schedule for testing new and refreshed vehicle models Only some tasks are destructive Most tasks are non-destructive but may have other constraints Test vehicles hand-built Build order Not all available at once Variety of models Frame, Market, Drivetrain, and Trim Project end date defined externally Limited personnel and facility resources

4. Constraints Temporal Calendar Ordering Resource Build Pitch Exclusive Destructive

5. Aurora Scheduling Framework Create a high-quality schedule Based on a model of temporal, calendar, ordering, and resource constraints Uses graph analysis techniques and heuristic-based scheduling Customized for domain Handle special kinds of tasks Exclusive, Destructive Minimize the number of vehicles required Select the types of vehicles built Select a build order for the vehicles

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8. Scheduling UI

9. Initial Schedule by Resource

10. Scheduling Framework Components Schedule Initialization Preprocessor Prioritizer Scheduling Loop Priortizier Scheduler Quality Criterion Conflict Manager Schedule Finalization Postprocessor

11. Differences From Prototype Testing on more complex models that require over 100 vehicles Utilizing facility and personnel constraints when creating a schedule Supporting the transition of the software into the hands of the actual planners

12. Domain Specific Customization User Interface Wizard Model Verification during Import Build Pitch Manage Vehicles Long Tasks Optimization Dashboard Scheduling Components

13. Wizard

14. Build Pitch

15. Manage Vehicles

16. Long Tasks

17. Optimization Dashboard

18. Scheduling Component Customization Preprocessor Override project end date Prioritizer Exclusive Task Long Task Destructive Task Tight Window End Based Load Based Subsequent Duration

19. Methods Actual Model ~340 tasks ~4000 days of work ~30-50 vehicle types Manual Solution Not attempted

20. Results Aurora Solution 60-200 Vehicles Adhere to all constraints Represents 6% reduction from best estimate Prototype found 12% reduction in direct comparison Schedule created in 2 minutes from model vs. days of labor Spend time using ‘What-if’ capability further improve the schedule Time Build Pitch Negotiation

21. Optimized Schedule

22. Deployment Deployed and in use by novice planners Previous solution no longer used Integrated with enterprise system Input data extracted from external data Results exported to corporate format Providing huge savings and other benefits with every new test suite

23. Conclusion Complex, real-world, scheduling problem Added domain-specific heuristics to a general intelligent scheduling framework Added help for novice planners Generated schedule for vehicle testing Significant reduction in the number of prototype vehicles required Still completed in the given timeframe Extend to multiple projects in future work