Create a Cross-Functional Flowchart

This work flow chart sample was redesigned from the picture "Simulation for earthquake disaster assessment" from the article "Simulation Workflows".
[iaas.uni-stuttgart.de/ forschung/ projects/ simtech/ sim-workflows.php]
" This simulation was developed to have an in depth understanding of the destructions and the decisions to be made in various phases of crisis management (Source: Mahdi Hashemi and Ali A. Alesheikh (2010). "Developing an agent based simulation model for earthquakes in the context of SDI." GSDI 12 World Conference. 19 – 22 October 2010. Singapour). The simulation process contains following major steps:
(1) All spatial information including satellite images (before and after the earthquake) and topographic/ cadastral maps of the area are mosaicked and georeferenced. The parts of the city that contain various levels of destructions are selected. Three types of features namely buildings, roads and recreational areas are classified and extracted from the satellite images.
(2) The governing factors of destructions are identified; a mathematical model that integrates the factors is constructed.
(3) The simulation is constructed for various parameter values (different earthquake strength, time elapses, etc.)" [iaas.uni-stuttgart.de/ forschung/ projects/ simtech/ sim-workflows.php]
The example "Workflow diagram - Earthquake disaster assessment" was drawn using the ConceptDraw PRO diagramming and vector drawing software extended with the Workflow Diagrams solution from the Business Processes area of ConceptDraw Solution Park.

This logistic flow chart sample shows a board design for the beer distribution game.
It was designed on the base of the Wikimedia Commons file: Beer Distribution Game Board.JPG. [commons.wikimedia.org/ wiki/ File:Beer_ Distribution_ Game_ Board.JPG]
This file is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license. [creativecommons.org/ licenses/ by-sa/ 3.0/ deed.en]
"The beer distribution game (also known as the beer game) is an experiential learning business simulation game created by a group of professors at MIT Sloan School of Management in early 1960s to demonstrate a number of key principles of supply chain management. The game is played by teams of at least four players, often in heated competition, and takes at least one hour to complete. A debriefing session of roughly equivalent length typically follows to review the results of each team and discuss the lessons involved.
The purpose of the game is to understand the distribution side dynamics of a multi-echelon supply chain used to distribute a single item, in this case, cases of beer." [Beer distribution game. Wikipedia]
The logistic flowchart example "Beer distribution game" was created using ConceptDraw PRO diagramming and vector drawing software extended with the Logistics Flow Charts solution from the Business Processes area of ConceptDraw Solution Park.

This work flow chart sample was redesigned from the picture "Weather Forecast" from the article "Simulation Workflows".
[iaas.uni-stuttgart.de/ forschung/ projects/ simtech/ sim-workflows.php]
"(1) The weather is predicted for a particular geological area. Hence, the workflow is fed with a model of the geophysical environment of ground, air and water for a requested area.
(2) Over a specified period of time (e.g. 6 hours) several different variables are measured and observed. Ground stations, ships, airplanes, weather balloons, satellites and buoys measure the air pressure, air/ water temperature, wind velocity, air humidity, vertical temperature profiles, cloud velocity, rain fall, and more.
(3) This data needs to be collected from the different sources and stored for later access.
(4) The collected data is analyzed and transformed into a common format (e.g. Fahrenheit to Celsius scale). The normalized values are used to create the current state of the atmosphere.
(5) Then, a numerical weather forecast is made based on mathematical-physical models (e.g. GFS - Global Forecast System, UKMO - United Kingdom MOdel, GME - global model of Deutscher Wetterdienst). The environmental area needs to be discretized beforehand using grid cells. The physical parameters measured in Step 2 are exposed in 3D space as timely function. This leads to a system of partial differential equations reflecting the physical relations that is solved numerically.
(6) The results of the numerical models are complemented with a statistical interpretation (e.g. with MOS - Model-Output-Statistics). That means the forecast result of the numerical models is compared to statistical weather data. Known forecast failures are corrected.
(7) The numerical post-processing is done with DMO (Direct Model Output): the numerical results are interpolated for specific geological locations.
(8) Additionally, a statistical post-processing step removes failures of measuring devices (e.g. using KALMAN filters).
(9) The statistical interpretation and the numerical results are then observed and interpreted by meteorologists based on their subjective experiences.
(10) Finally, the weather forecast is visualized and presented to interested people." [iaas.uni-stuttgart.de/ forschung/ projects/ simtech/ sim-workflows.php]
The example "Workflow diagram - Weather forecast" was drawn using the ConceptDraw PRO diagramming and vector drawing software extended with the Workflow Diagrams solution from the Business Processes area of ConceptDraw Solution Park.