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Queueingtheoryinsoftware development Håkan Forss - hakan.forss@avegagroup.se - @hakanforss
Or
What can traffic inteach you about yourdevelopment process Håkan Forss - hakan.forss@avegagroup.se - @hakanforss
Little’s Law Work-in-Process Throughput Cycle Time =
Little’s Law 12 12 / min 1 min =
Little’s Law 6 12 / min 0,5 min=
Little’s Law 24 12 / min 2 min =
8 cars / min 4 cars / min With less work-in-progress Shorter cycle time Faster feedback Makes problems visible faster
TheoryofConstraints
5
Don’t allow inertia to cause a system constraint.
Capacity = 4 Capacity = 6 Capacity = 6 Throughput = 4 Bottlenecks You can never go faster than your bottleneck
Bottlenecks Throughput = 2 You can never go faster than your bottleneck Do whatever you can to make your bottleneck 100% utilized  Try your hardest to avoid problems at you bottleneck  You can’t make up for lost capacity at you bottleneck
Throughput = 4 You can never go faster than your bottleneck As long as capacity in front of the bottleneck is equal to or grater than the bottleneck you will go as fast as your bottleneck Full use of a higher capacity in front of the bottleneck will make cycle time go up Bottlenecks
Bottlenecks Throughput = 4 You can never go faster than your bottleneck As long as capacity is equal to or grater after the bottleneck you will go as fast as your bottleneck Higher capacity after the bottleneck than at the bottleneck will not improve throughput
Non-instantavailabilityresource A resource that is not available all the time
Non-instantavailabilityresource & bottleneck
You can never go faster than your bottleneck Balance demand against throughput to keep work-in-progress low Low work-in-progress Keeps cycle time down  Makes bottlenecks visible faster
Slow down to go faster  Slowing down can stabilize the process flow A stable process can go faster
Håkan Forss Mail: hakan.forss@avegagroup.se Twitter: @hakanforss Blog: http://hakanforss.wordpress.com/

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Queueing theory in software development - ALEBathtub 2011-06-30

  • 1. Queueingtheoryinsoftware development Håkan Forss - hakan.forss@avegagroup.se - @hakanforss
  • 2. Or
  • 3. What can traffic inteach you about yourdevelopment process Håkan Forss - hakan.forss@avegagroup.se - @hakanforss
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9. Little’s Law Work-in-Process Throughput Cycle Time =
  • 10. Little’s Law 12 12 / min 1 min =
  • 11. Little’s Law 6 12 / min 0,5 min=
  • 12. Little’s Law 24 12 / min 2 min =
  • 13. 8 cars / min 4 cars / min With less work-in-progress Shorter cycle time Faster feedback Makes problems visible faster
  • 14.
  • 16.
  • 17.
  • 18. 5
  • 19. Don’t allow inertia to cause a system constraint.
  • 20. Capacity = 4 Capacity = 6 Capacity = 6 Throughput = 4 Bottlenecks You can never go faster than your bottleneck
  • 21. Bottlenecks Throughput = 2 You can never go faster than your bottleneck Do whatever you can to make your bottleneck 100% utilized Try your hardest to avoid problems at you bottleneck You can’t make up for lost capacity at you bottleneck
  • 22. Throughput = 4 You can never go faster than your bottleneck As long as capacity in front of the bottleneck is equal to or grater than the bottleneck you will go as fast as your bottleneck Full use of a higher capacity in front of the bottleneck will make cycle time go up Bottlenecks
  • 23. Bottlenecks Throughput = 4 You can never go faster than your bottleneck As long as capacity is equal to or grater after the bottleneck you will go as fast as your bottleneck Higher capacity after the bottleneck than at the bottleneck will not improve throughput
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32. Non-instantavailabilityresource A resource that is not available all the time
  • 34.
  • 35.
  • 36.
  • 37.
  • 38. You can never go faster than your bottleneck Balance demand against throughput to keep work-in-progress low Low work-in-progress Keeps cycle time down Makes bottlenecks visible faster
  • 39.
  • 40. Slow down to go faster Slowing down can stabilize the process flow A stable process can go faster
  • 41.
  • 42.
  • 43. Håkan Forss Mail: hakan.forss@avegagroup.se Twitter: @hakanforss Blog: http://hakanforss.wordpress.com/

Notes de l'éditeur

  1. There are two different types of bottlenecks: - Capacity contraint resource - a resource limited by capacity, like a bottle - non instantly available resource - a resource that is not available all the time