![]() I think it is already clear that this task would either take a great deal of time for a human being or lead to a suboptimal result.Īs complexity increases, we quickly move into areas that are no longer feasible for us humans.įinally, I would like to present a small but quite helpful tool of the Behavioral Modelling Extension. At the same time, a filling line should be placed at 1.19 l. We would like to have our capacity larger than or equal to 3.71 l. The initial situation is a very limited construction space, which allows only little margin. In the study here, there are 5 different design variables – including one angle and 2 design conditions – that we want to achieve. This belongs to a snowmobile from Polaris. As a brief extended example, I would like to show you an oil tank. For a simple bottle maybe a bit of overkill, but definitely an illustrative example.īut think more about the complex problems you can manage with this. You can see in the screenshot what exactly I have specified.Īfter the study is connected, we see that the dimension “d7:BLOG_BMX” has been set to exactly 122.917 mm.Īs you can see, it is very easy to actually create a perfect result for our level with the Creo Parametric – Behavioral Modelling Extension (BMX). We stipulate here that our volume should be exactly 500,000 mm3. Next, we use the “volume” measurement from our sensitivity study. We use the measure “d7:BLOG_BMX”, which controls the offset of the level “fill level” this also references the sketch that creates the level stroke. In our example, this is only a single measure, of course you can use as many as you like here. To do this, we first give the “Feasibility Study” tool which dimension it can change. With the Creo BMX, however, this is now a very, very small problem. With a rule geometry, this would not be a problem, but here we would have to try a lot until the result would fit. Next, we’ll look at how to place the level marker at exactly 0.5 l. The change is linear here if we were to change an angle here, we could see a progressive or degressive change in volume. Roughly above the thumb we see that the change of the parameter “d56:FLASCHE” by 3 millimeters leads to a change in volume by about 50 milliliters. The result is shown in the graph at the top right of the screenshot. For “d56:FLASCHE” we now specify the range spanning from 100mm to 115mm and in how many segments the analysis should be carried out we set that on 20. In our case, this is the measurement “volume” that we have placed as a feature in the model tree and the sketch dimension “d56:FLASCHE”. To this end, we tell the tool that, on the one hand, it should measure the volume and on the other hand, which parameter should be analyzed. We can do this through a sensitivity study. ![]() The filling level of the bottle is controlled via the fill level.įirst, we look at how changing a parameter affects the volume of the bottle. In the screenshot below you can see that I have modelled the bottle and already prepared it with the volume of the liquid. Now, of course, a volume calculation is absolutely nothing special anymore. This means that even a normal volume calculation would involve a considerable effort. The silhouette of our bottle was given to us by a designer and follows a non-regular or no cylindrical shape. Our bottle must not be higher than 200 millimeters and must not exceed 115 mm in diameter. In addition, we would like level markings at 0.5 l and 1 l. This bottle should have 1 l capacity – or even a bit more. Our job as a designer today is to design a bottle. Let’s take a look at the functions of the PTC Creo Parametric Behavioral Modeling Extension (BMX) in a simple example: ![]() With Behavioral Modeling Extension, Creo Parametric (formerly Pro/ENGINEER Wildfire) offers the ability to provide top-level tools exactly in these situations. In simple situations, this may still be applicable.īut at the latest, when it comes to combinations that are in the triple-digit decimal range, it will be difficult for us humans. Of course, there is always the possibility of trial-and-error. Personally I believe that everyone who actively designs products for today’s highly competitive and optimized market knows the problem of determining the optimal combination of different dimensions and parameters. Design automation for various design goals with PTC Creo Parametric Behavioral Modeling Extension (BMX)
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