Some topics in surface texture and tribology are challenging to visualize. These short videos and animations help to cut through the math to make the key messages easier to grasp and retain.
If you rely on average roughness (Ra) to control your surfaces, check out this short animation. It shows that very different surfaces can all have the same Ra value…and Ra alone can’t tell you which one you’ve manufactured!
Average Roughness—in surface texture measurement, it’s one of the most frequently specified surface roughness parameters. In this video we look at how average roughness (Ra, or Sa) is calculated. We look at what Ra can — and can’t — tell us about a surface. And, we discuss the differences between Ra, Sa, and related parameters that you may encounter in surface texture analysis software.
“Roughness” can mean a lot of things, but in surface texture analysis, it has a very specific meaning.
In this short video we look at how 2D and 3D surface texture data can be filtered down to a band of spatial wavelengths that we can analyze as “surface roughness.” It’s a fundamental concept of surface texture analysis, and the basis for our upcoming videos on surface roughness measurement as well.
It seems like it should be easier to push a heavy block if it’s standing on end, rather than laying on its face…and yet this isn’t always the case. The reason why lies in the difference between the “real area of contact” and the “apparent area of contact.” In this video we zoom in on surface roughness to understand what’s really happening when rigid surfaces come into contact.
Surface texture can be described as a spectrum of spatial wavelengths. “Filtering” is the process to isolate the wavelengths that matter for our application. But what does that really look like? One way to visualize it is to think of sorting different sized stones. In this short animation we show how we can use that analogy to visualize filtering into surface roughness, waviness, or as many bands as necessary for the application.
In this brief animation we look at surface texture as a spectrum of spatial wavelengths. We can use cutoff wavelengths to examine different ranges within that spectrum to spot differences in the surface texture that we might miss if we only track the overall average roughness. When we can see the differences, we can take steps to control them. And that’s the key to a smooth finish.