Simio Simulation software for production and logistics

Project organization and ribbons in Simio

The tabs in Simio software split every project into separate sections (or project facades) right from the start. “Facility” is the place where the user builds the model layout. It includes resources, object instances, and the full animation of the model. In “Processes” there are actions and algorithms controlling the objects in the model. In “Definitions” there are variables and other constructs or declarations that are used in the model objects. “Data” organizes all model data into relational tables with its connections to data sources. “Results” section provides a comprehensive presentation of your model’s results. Finally “Planning” is used for the risk based analyzes.

Simio objects and libraries

Simio’s object-based paradigm concept radically changes the way simulation models are created and used. Flexible objects from Simio libraries are adjustable with their properties. Users can add processes to reach a desired level of detail, all without programming.

Most users will find the flexible objects in the Standard Library very handy. While advanced users will subclass these and redesign to fit their particular purpose.

Simio Logic

After objects are placed in the Facility tab they “know” what to do. Their logic is already predefined. Since each modeled system can be very individual, Simio allows for flexible object customization with properties and add-on processes. In this manner, objects in Simio are modified with short process snippets. These snippets are placed with surgical precision exactly where needed.

The plug’n’play logic definition saves the modeler a lot of time. This is because the objects are not created from scratch each time.

Relational data tables

Simio stores data in relational tables with 1: n or n:n relationships (e.g. order and order detail), making data organization efficient and easy to use. A new job in the model links directly to its corresponding order. When querying the order table, it retrieves only the relevant details. These include product and quantity for that job.

There is no need for a complex and CPU intensive search through data sets. Many thousands of rows would be a common practice for other simulation products on the market. This saves time, saves the model from errors and speeds up simulation runs.

Using big data in Simio

Every extra piece of company data contributes to a better understanding of the processes in the company. Thanks to the flexible modeling way in Simio all this data can then be directly part of the model. This way even more realistic simulation runs can be carried out of the current production system.

Each simulation run generates results that can be easily transferred to your ERP system using Simio’s import-export feature.

Interactive Dashboards in Simio

The dashboards provide a customized display of aggregated results using tables, charts, maps and images.

The simulation output data can be selected interactively between different forms of a dashboard. This ensures that only selected data appears there. For example see a machine Cut1 label selected in the picture. The chart shows then how its value has been changing during the simulation run.

Gantt diagram in Simio

Simio Enterprise Edition includes Gantt diagrams. These diagrams show how products and orders flow through the model during the simulation run. Just a quick look on the diagram suffices to see how the run was. The orders are waiting, seizing and releasing resources. The resource view shows which orders are processed on each resource one by one. Another use of Gantt is for planing, see the Scheduling section for more information.

Experiment and scenarios in Simio

Simio offers many innovative features for analyzing your simulation results. You can define experiments with multiple scenarios and have them run automatically in parallel on a multi-core processor. Simio uses powerful analytics capabilities, including optimization adds-on to automatically compare the scenarios.

Innovative SMORE diagrams are used to show the impact of errors and risks across different scenarios.

Use all CPUs

To evaluate a simulation model it is necessary to run many scenarios and for every scenario to run multiple replications. It is common to define 1000 simulation runs for an experiment.

To accelerate model experiments, Simio runs simulations parallel on all available processor cores, using one core per run. It can also use CPUs from other computers on the network.