Getting the time right: improving MES estimates for AM
May 01, 2018 | Categories: Member News
Previously, we simply relied on volume * previous print times (which we gather from print times we have previously monitored) to estimate the time it would take to print a certain 3D model. That’s now changing. We’re keeping the machine learning element and are multiplying them not only with volume but also factoring in material, resolution, and infill. These added variables will ensure that you get reliable and accurate time estimations for your orders.
This is only the start. We are working to bring this dynamic system to other processes such as polishing, support removal and others. We also know that even the factors used to determine print time in this Version 2 may not represent the full list. Our next phase is to let the data tell us more about those factors itself, rather than guessing.
One last update that we’re proud of: we’ve made it even easier to export your data. You can already do so with our API toolkit. Now we’ve started adding CSV export options. The first is to export a list of all orders. You can even enter a time period you’re interested in.
These steps forward are mostly heralded by customer feedback on new features or improvements they’d like to see in their perfect MES solution. If you want to contribute and make our platform better and better, don’t hesitate to contact our CMO Frank Speck at firstname.lastname@example.org.
Take a look at our modular platform here.