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© 2024 Samd Guizani

## WHAT IS IT?

This model aims to illustrate the dynamics of task backlogs in an office or industrial workshop setting. It helps identify potential bottlenecks, such as insufficient workers or workstations, that can hinder the processing of tasks.

## HOW IT WORKS

- Tasks (in form of boxes) are generated randomly and periodically following a Poisson distribution. Each task belongs to a group (identified by a Task ID) which defines its required processing duration and the specific workstation it needs to be processed at.
- Tasks are dispatched to available workstations, and workers are assigned to these workstations where tasks are awaiting processing. Only workers with the required qualifications for a specific task can be assigned to it.

## HOW TO USE IT

To set up the simulation, user can define:

- The number of workstations for each group of tasks.
- The number of workers qualified for each type of task. Workers can be defined to perform multiple types of tasks.
- The processing duration for each type of task and their creation rate, adjustable via sliders. These parameters can also be modified during the simulation.

During the simulation, user can monitor:

- The backlog of each group of tasks (i.e., the count of unprocessed tasks in each group). This information is available in monitors and plots.
- The occupation of workers (the count of available workers over time) in a plot.
- The occupation of workstations (the count of available workstations for each task group over time) in a plot.

## THINGS TO NOTICE

Notice that task backlogs exhibit transient behaviors, with temporary accumulations of tasks in certain groups. This is due to the randomness of task generation (using a Poisson distribution) and the randomness of worker assignment to tasks.

When a bottleneck exists for a given Task ID, its backloggrows continuously due to the accumulation of unprocessed tasks.

## THINGS TO TRY

By testing various scenarios involving the number of workers, their qualification set, and the number of workstations, user can identify bottlenecks in the task processing flow.

## EXTENDING THE MODEL

The model can be extended to accommodate more groups of tasks, though managing worker qualifications may become more complex.

Other potential extensions include experimenting with different worker assignment rules: Currently, workers, provided they satisfy the required task qualification, are randomly assigned to available workstations with tasks. Implementing prioritization rules or a First-In-First-Out (FIFO) principle could alter the results.

## NETLOGO FEATURES

No information to report

## RELATED MODELS

NetLogo library: Road traffic models

## CREDITS AND REFERENCES

None

© 2024 Samd Guizani

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