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On Cyclic Plans for Scheduling of a Smart Card Personalisation System Tim Nieberg Universiteit Twente, EWI/TW DWMP-Group.

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Presentation on theme: "On Cyclic Plans for Scheduling of a Smart Card Personalisation System Tim Nieberg Universiteit Twente, EWI/TW DWMP-Group."— Presentation transcript:

1 On Cyclic Plans for Scheduling of a Smart Card Personalisation System Tim Nieberg Universiteit Twente, EWI/TW DWMP-Group

2 Overview / Objectives Give abstract model of schedule  Define (L,f)-cyclic schedule Bounds on Cycle-Time Special Schedules  Tight Loading  Single-Mode Optimal Plans for Case Study

3 Model of Personalisation System n Smart Cards k Pers. Stations  Loading/Unloading  Personalisation m Graphical Machines  Processing Time Conveyor Belt with n+k+2 slots underneath J 1,…,J n S 1,…,S k  P in,P out  P pers M 1,…,M m  p j  p max := max p j n>1’000 k=4,8,16,32  ½  10-50 k=5  p PR =3  p FO =3/2  p L =4

4 Model of Personalisation System

5 Assumptions w.r.t. Case Study For now, we assume  No time needed for placing cards onto belt  No gap b/w personalisation and graphical treatment  Flip-Over machines use single slot Equivalent to real case  No faulty cards

6 Characterization of Schedules

7 Cyclic Schedules

8 (L,f)-cyclic Schedules Definition:  A cyclic schedule that involves placing L smart cards onto the conveyor belt, and that uses f free slots, is called (L,f)-cyclic schedule. Maximizing Throughput Minimizing Cycle Time

9 Lower Bounds on Cycle Time -> Personalisation Consider personalisation part of system Claim 1:  Any cyclic schedule has cycle time of at least P in +P out +P pers +1. This is the minimal time to personalise a smart card in one of the personalisation stations.

10 Lower Bounds on Cycle Time -> Graphical Treatment Consider feasible, (L,f)-cyclic schedule  Belt has to advance L+f times  + Lp max for bottleneck machine  + other f free slots under bottleneck machine Some machine(s) have to process max F denotes F th largest processing time in case that F free slots are arbitrarily presented to graphical machines M 1,…,M m i.e.

11 Lower Bounds on Cycle Time -> Graphical Treatment Claim 2:  An (L,f)-cyclic schedule has a cycle time of at least Advancement of Belt Processing Bottleneck Machine LB on Processing Non-Bottleneck

12 Special Schedules: Tight Loading (k,0)-cyclic schedule  All k personalisation stations loaded and unloaded at once

13 Special Schedules: Tight Loading (k,0)-cyclic schedule  All k personalisation stations loaded and unloaded at once

14 Special Schedules: Tight Loading (k,0)-cyclic schedule  All k personalisation stations loaded and unloaded at once

15 Tight Loading: Properties TL dominates any (L,0)-cyclic schedule  L>k: easy (split into subschedules)  L { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/14/4285782/slides/slide_15.jpg", "name": "Tight Loading: Properties TL dominates any (L,0)-cyclic schedule  L>k: easy (split into subschedules)  Lk: easy (split into subschedules)  L

16 Theorem 1:  Any (k,0)-cyclic schedule only loads and unloads from and to the same slot on the belt. Idea of proof: Any other schedule results in infeasibility after insertion of at most k new cards. Corollary:  Any other schedule uses at least one free slot per k smart cards. Uniqueness of Tight Loading

17 (Super) Single Mode At beginning of cycle, a free slot is inserted into system  1.) Personalisation Station unloads if free slot is advanced underneath  2.) Belt advances  3.) New card is now loaded into Pers. Station Single Mode is event-driven  Advance belt as soon as all task have been completed Single Mode respects order of smart cards  Simple inductive arguement

18 (Super) Single Mode SM defines (k,1)-cyclic schedule When personalisation is bottleneck, i.e. P pers +P in +P out > k + k p max + max 1, then SM is optimal  Pf: Claim 1 => each Pers. Station is optimally utilized.

19 Optimal Schedules for Case Study Overview of bounds obtained thus far (for (k,f)-cyclic schedules): From Claim 1:

20 Optimal Schedules for Case Study Tight Loading has Cycle Time Compare with LB

21 Optimal Schedules for Case Study (k,0)-cyclic schedule does not meet bound for any P pers > 10 in case study By Theorem 1:  Improvement, if exist must use at least one free slot per k smart cards  => Single Mode

22 Optimal Plans for Case Study Cycle Times for Single Mode

23 Optimal Plans for Case Study Cycle Times for Single Mode

24 Optimal Plans for Case Study Cycle Times for Single Mode

25 Optimal Plans for Case Study Note that inserting even more free slots must result in plans with strictly greater cycle time

26 Notes on the Assumptions Some assumptions made can be “revoked”  Loading/Unloading of conveyor belt always takes less time than bottleneck task of graphical treatment  Gap b/w Personalisation Stations and Graphical Treatment does not affect arguements presented

27 Conclusions A simple characterization of cyclic schedules by the number of free slots they use has been presented  This characterization was used to show that there exists only one (k,0)-cyclic schedule (Tight Loading)  Lower bounds on the cycle time of (L,f)-cyclic schedules were given Using destructive bounding methods, the instances of the CYBERNETIX case study were solved at optimality

28 Thank you for your attention… T.Nieberg@utwente.nl


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