Smart Card Personalisation Machine in UPPAAL

1. Smart Card Personalisation Machine in UPPAAL Cybernetix case study for AMETIST project

2. Outline • Informal description • UPPAAL model • General description of model • Comparison with SMV model • Model • Demo • Tested configurations • Results • List of experiments • Result of experiments • Plans • Conclusions

3. Informal description • CYBERNETIX Case Study, Informal description Sarah ALBERT, Cybernetix Recherche • Smart Card Personalisation Machine in SMV, AMETIST: Cybernetix Case Study Biniam GEBREMICHAEL, Frits VAANDRAGER, University of Nijmegen • Smart Card Personalisation Machine Smart card personalisation machine takes a pile of the blank smart cards as a raw material, programs them with the personalised data, prints them and tests them. • Objectives • Synthesis of correct and optimal schedules • Model&tool for Cybernetix

4. UPPAAL model • Simplified configuration • Conveyor • Unloader/Loader • Personalisation stations • Several versions • Chronological ordering by unloader • Chronological ordering by personalisation stations • Configurable parameters • conveyor length • number and positions of personalisation stations • temporal aspects: personalisation time, conveyor speed, unload/load time • Standard UPPAAL(timed automata with extensions)

5. Comparison with SMV model • Smart Card Personalisation Machine in SMV, AMETIST: Cybernetix Case Study Biniam GEBREMICHAEL, Frits VAANDRAGER, University of Nijmegen • Both models are very abstract models • Differences

6. Conveyor: belt and conveyor movement • int[0,2*CARDS] c[CELLS] - the conveyor belt, where • CELLS is the length of the conveyor belt, (0..CELLS-1) • CARDS – the number of the cards in the batch (1..CARDS – unpersonalised cards, CARDS+1..2*CARDS – personalised)

7. Unloader: unloads the cards on the conveyor one by one

8. Loader: removes the cards from the conveyor one by one

9. Personalisation station

10. Demonstration on UPPAAL

11. Tested configurations • Chronological ordering • by unloader • by personalisation stations • Number of personalisation stations and cards in the batch • 2 personalisation stations, 2..8 cards • 3 personalisation stations, 2..6 cards • 4 personalisation stations, 2..5 cards • Timing information • personalisation time = 10 time units • unloading/loading time = 2 time units • one conveyor step = 1 time unit

12. Results: Experiments list personalisation = 10, unloading/loading = 2 time units, conveyor step = 1

13. Results:2 stations, 6 cards and 3 stations, 5 cards

14. Results: 4 stations4 cards and 5 cards

15. Interpretation of results • Unloading/loading stations are bottlenecks – the cards should be spread to get better results • If unloading/loading is instant, the “super single mode” and the “batches” algorithms are both “optimal” • Several schedules can be optimal; to find the scheduling algorithm it would be useful to have tools, which allow to get all optimal traces

16. Plans • Models with more stations and more cards, several batches of cards • Models with bi-directional conveyor • Models with • Graphical personalisation stations • Testing & reject stations • Flip over stations • Specialised versions of UPPAAL • Other tools

17. Conclusions: early stage • Smart card personalisation machine • Different abstractions of the system can be made • A fixed benchmark configuration is desirable to compare the results • More information about the system would be useful • UPPAAL • It is possible to model the system in UPPAAL • For small numbers of stations and cards it is possible to find optimal schedules automatically • For automatic analysis of larger systems additional features could be useful • diagnostic information (number of states, precise run-time information) • batch mode • access to the underlying transition system • guided search • question: is UPPAAL a right tool to model such systems (discrete time systems, deterministic systems)

18. That’s all...