The model takes into account clothing production and textile waste on a global scale while incorporating Vancouver's own "Fast Fashion" issue into the model.
Please refer to the notes for each variable and stock for more information and to see which links were hidden from the model.
From Werner Ulrich's JORS Articles Operational research and critical systems thinking – an integrated perspective. Part 1: OR as applied systems thinking. Journal of the Operational Research Society advance online publication (14 December 2011). and Part 2 :OR as argumentative practice.
From Werner Ulrich's JORS Articles Operational research and critical systems thinking – an integrated perspective. Part 1: OR as applied systems thinking. Journal of the Operational Research Society advance online publication (14 December 2011). and Part 2 :OR as argumentative practice.
This simulation allows you to compare different approaches to influence flow, the Flow Times and the throughput of a work process.
By adjusting the sliders below you can
observe the work process without any work in process limitations (WIP Limits),
with process step specific WIP Limits* (work state WIP limits),
or you may want to see the impact of the Tameflow approach with Kanban Token and Replenishment Token
or see the impact of the Drum-Buffer-Rope** method.
* Well know in (agile) Kanban
** Known in the physical world of factory production
The "Tameflow approach" using Kanban Token and Replenishment Token as well as the Drum-Buffer-Rope method take oth the Constraint (the weakest link of the work process) into consideration when pulling in new work items into the delivery "system".
You can also simulate the effects of PUSH instead of PULL.
Feel free to play around and recognize the different effects of work scheduling methods.
If you have questions or feedback get in touch via twitter @swilluda
The work flow itself
Look at the simulation as if you would look on a kanban board.
The simulation mimics a "typical" software delivery process.
From left to right you find the following ten process steps.
Input Queue (Backlog)
Selected for work (waiting for analysis or work break down)
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.
We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.
I start with these parameters: Wolf Death Rate = 0.15 Wolf Birth Rate = 0.0187963 Moose Birth Rate = 0.4 Carrying Capacity = 2000 Initial Moose: 563 Initial Wolves: 20
I used RK-4 with step-size 0.1, from 1959 for 60 years.
The moose birth flow is logistic, MBR*M*(1-M/K) Moose death flow is Kill Rate (in Moose/Year) Wolf birth flow is WBR*Kill Rate (in Wolves/Year) Wolf death flow is WDR*W
equations I used in kill rate :
power model - 12*0.1251361120909615*([Moose]/[Wolves])^.44491970277839954*[Wolves]
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.
We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.
I start with these parameters: Wolf Death Rate = 0.15 Wolf Birth Rate = 0.0187963 Moose Birth Rate = 0.4 Carrying Capacity = 2000 Initial Moose: 563 Initial Wolves: 20
I used RK-4 with step-size 0.1, from 1959 for 60 years.
The moose birth flow is logistic, MBR*M*(1-M/K) Moose death flow is Kill Rate (in Moose/Year) Wolf birth flow is WBR*Kill Rate (in Wolves/Year) Wolf death flow is WDR*W
Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Launchpad for insights related to Systems and Complexity in general and Systems Science for Health in particular. Current key participants are public health researchers, health service managers, clinicians, and mental health policy makers and practitioners
