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Modeling Kanban Scheduling in Systems of Systems. Alexey Tregubov, Jo Ann Lane. Outline. Modeling Kanban scheduling in System of Systems: Why do we need to model? Overview of KSS Network Key aspects of Kanban scheduling technique Simulation model Example of KSS Network

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Modeling Kanban Scheduling in Systems of Systems


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outline
Outline

Modeling Kanban scheduling in System of Systems:

  • Why do we need to model?
  • Overview of KSS Network
  • Key aspects of Kanban scheduling technique
  • Simulation model
  • Example of KSS Network
  • Results & future work
why do we need to model
Why do we need to model?

Applications of modeling in System of System environments:

  • Hypothesis testing
  • Process improvement
  • Business decision support
  • Cost and effort estimation
key aspects of kanban scheduling
Key aspects of Kanban scheduling

Kanban principles embedded in prioritization algorithm:

  • Eliminate waste
    • Minimize context switching
    • Limit work in progress
  • Make process more visible and transparent
    • Kanban boards
  • Increased value delivered earlier
    • Value-based work prioritization
  • Reduce governance overhead
key aspects of kanban scheduling continued
Key aspects of Kanbanscheduling (continued)

Work prioritization algorithm based on the following:

  • All work items (WI) prioritized according to their business value
  • Every WI has a class of service: Standard, Important, Date Certain, Critical Expedite
  • Limiting work in progress: work in progress is never interrupted unless new work has a Critical class of service
simulation model
Simulation model

Discrete event simulation:

  • Inputs:
    • Event scenario: a sequence of events that describes how network evolves over course of their execution
    • Team configuration: structure of teams, resource/specialties allocation
    • Simulation configuration: stop condition
  • Outputs:
    • Sequence of network states
    • Analysis: various indicators of effectiveness
simulation model definitions
Simulation model: definitions

Discrete event simulation – network state & transition algorithm

Network state objects:

  • Kanban board – demand log, work items in progress
  • Team – group of resources (e.g. software development team)
  • Work item – task that requires effort to completed
  • Aggregation Nodes – logical group of work items, such as requirements, capabilities
  • Kanban network – teams, Kanban board, and their work items

Transition algorithm:

  • Trigger events according to the scenario
  • Apply work prioritization algorithm
conclusion results
Conclusion: results
  • Simulation model
  • Simulator implementation: KSS Simulator
  • Two prioritization algorithms implemented
  • Several scenarios analyzed
conclusion future work
Conclusion: future work
  • Pilot the Kanban scheduling with several organizations
  • Fine-tune the simulator using empirical data and organizations feed back
  • Scale up the cases we run through the simulator
  • Refine and calibrate cost models