Disappearing SIMUL8 Graphs

Graphs have a tendency to disappear from the SIMUL8 screen as you work with a model. We often hear from users who want to know how to 'fix' the problem. A second symptom could be that SIMUL8 appears to 'lock up".

While this occurrence may seem disconcerting at first, there is actually nothing to fix. The graphs are still there - they've just slipped out of sight behind the main simulation window. The best way to retrieve them is to press ALT-TAB as if you were going to switch to a different application. This triggers SIMUL8 to refresh itself and therefore bring the dialogs to the front.

You can find comprehensive information on this topic and many more in Learning SIMUL8: The Complete Guide, as well as through our innovative SIMUL8 training programs

Model Validation

The topic of how to validate a simulation model has been well-studied and oft written about in academic circles. We’ll defer to existing texts on that topic as it is beyond the scope of this document. (Averill and Law in their excellent general simulation text, for example, have an excellent discussion of the topic). We will, however, share a few practical types specific to the testing and validation of call center specific models.

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How Low Can You Go? Using Simulation to Determine Appropriate Inventory Levels

Proper inventory levels are critical to maximizing your manufacturing system’s performance; but what level of inventory is best? Too much inventory will add cost and increase cycle time. Too little inventory will jeopardize total output. Achieving good system performance depends upon a very difficult and often non-intuitive exercise in balancing capacity against demand. This exercise is made all the more difficult by the random variability inherent in any real system. Fortunately, there is a tool – discrete event simulation - that gives you the very valuable ability to understand how variability and randomness affect your process. Perhaps most importantly, however, simulation allows you to experiment with various inventory policies in determining the best balance for your particular system, all without having to implement non-optimal choices in the real system.

After a review of basic issues in inventory management, we provide an overview of simulation in this context. We will discuss simple simulation examples as well as case studies from manufacturing, service, and supply chain analysis. We conclude by offering advice for implementing simulation in your organization.

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Modeling Variability

A recent project highlighted a different way of needing to look at variability.  The normal practise of gather, analysing and entering process times into SIMUL8 just did not work. The normal method would be:

1. Collect data into a spreadsheet.
2. Manipulate the data if necessary to get it into the form of minutes per piece.
3. Paste the data into your favorite statistical software to identify the distribution which best represents the variability of your system.
4. Enter the resulting distribution into SIMUL8 as a work center's operation time.

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Simulation Optimization

Your Guidance System for Complex Decisions Under Uncertainty

Simulation has proven itself to be an incredibly useful tool for evaluating complex systems. Sometimes, however, you need to do more than just evaluate how a system will react under a given combination of conditions. Instead, what you really need to do is find the combination of conditions that will give you the 'best' possible system performance. To achieve this with a stand-alone simulation model, you will need to change model parameters, run each scenario and repetitively review results in the search for a satisfactory solution.

A simulation optimization algorithm works to automate this search procedure in an intelligent manner, saving you time and, if properly used, giving you superior results. In cases where there are many, many alternatives to evaluate, the automated guidance provided by a good simulation optimization tool can be a very welcome addition to your modeling arsenal.

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