Ariana

ARIANA is a generic graphical-user interface designed to provide Arena simulation users with a friendly and intuitive means of interacting with simulation models. ARIANA easily manages model inputs, scenarios, and outputs of Arena models. It advises the user on adequacy of number of replications and performs t-tests to compare system scenarios. ARIANA allows users to change input parameter values, set up and run experiments, and retrieve/view the results in spreadsheet view as well as graphical view, without the need to interact with the simulation model directly.

ARIANA was developed by utilizing over 20 years of expertise in development of simulation models and simulation-based decision support solutions to fulfill the needs of modelers and customers and to streamline simulation modeling and analysis processes.

 Ariana _Startup

Who uses ARIANA?

ARIANA was designed for two types of users: Arena simulation modeler "modelers" and Arena models user "users". The "modelers" build, verify, validate, and deliver simulation models; in some cases, they do analysis using the model, create simulation scenarios, compare scenarios, run statistics test, and deliver reports. The "users", on the other hand, do analysis through building what-if scenarios, run the simulation model, compare/analyze outputs, and create and build analysis reports.

 All _scenarios _screen _with _outputs 

ARIANA allows you to perform two specific analyses on the outputs of the simulation. These analyses are:

1- T-test (Unequal sample sizes, unequal variance) for determining if there is a significant difference between the values of the output parameters. In ARIANA, when t-test is selected, the output parameters that are significantly different from "Baseline" output parameters will be highlighted.

2- Precision Test for assessing adequacy of the number of replications. Precision is defined as the half-width of the confidence interval expressed as a percentage of the cumulative mean (Average) of the replications performed. The precision required for an adequate number of replications will depend on user criteria, but generally, a value between 5% and 10% is indicative of a sufficient number of replications to obtain significant results.

In addition to providing numerical outputs from the simulation model, ARIANA allows users to view results in graphical form. These graphs are populated each time ARIANA is opened using the files specified during GUI customization.

 Graphs1

ARIANA's chart interface is designed to facilitate immediate and painless visualization of data captured from a simulation model across as many scenarios as the user has defined. This powerful tool provides the means for side to side trend analysis and comparison. Granted the copious amounts of data that can be presented, the interface is built so the user can choose presentation type, scale both the X and the Y axis, and choose which scenarios to show at any given time. The user should consider which parameters to show together in the same graph, as the chart will automatically scale to the largest of the numbers; for best results it is recommended that similar data be shown in the same graph.

Benefits from Using ARIANA

  • Faster delivery of analysis results, reports, and charts.
  • Faster delivery of valid simulation models by an average of 30%.
  • Reduction in verification and validation time by an average of 20%.
  • Delivery of higher quality models and tools.
  • Significant reduction in model support time by an average of 60%.
  • Ability to run scenarios and generate output reports without relying on modelers.
  • Reduced possibility of errors when making changes to the model, 90-100% reduction.
  • Ability for any modeler or user to run scenarios and generate analysis reports.
  • Ability to quickly create and run scenarios while also highlighting data changes between scenarios as well as a selected baseline scenario.
  • Ability to compare simulation scenarios side by side.
  • Ability to run simulation scenarios in the background, thus being able to run hundreds of scenarios without being in front of the computer.
  • Ability to run statistical tests between scenarios such as t-tests and highlighting statistically significant differences.
  • Ability to focus on specific output parameters.
  • Ability to quickly rename input or output parameters.

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