Modeling Kanban Scheduling in Systems of Systems

Alexey Tregubov, Jo Ann Lane

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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

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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

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Health care example of KSS Network

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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

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Key aspects of Kanban scheduling (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

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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

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Simulation model: definitionsDiscrete 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

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Health care example

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Example: capabilities to requirements to products

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Example: network structure & scenario

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Example: outputs

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Example: workflow

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Example: result analysis Value:

0 5 10 15 20 25 30 350.00

200.00

400.00

600.00

800.00

1000.00

1200.00

random kss

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Conclusion: results

Simulation model Simulator implementation: KSS Simulator Two prioritization algorithms implemented Several scenarios analyzed

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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

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Questions & answers