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March 22, 2026      News      9061

In FDM 3D printing, when aiming for a smooth top surface, many people's first reaction is to enable "ironing"—the nozzle makes an extra pass to smooth out layer lines. But this takes extra time and is highly dependent on settings.

Maker "Make Wonderful Things" decided to take a different approach: directly optimize the parameters so the top layer itself prints perfectly.

Finding Answers from 19,200 Combinations

He focused on three key parameters: top surface line width, flow rate, and print speed. Even using practical increments, this created 19,200 possible combinations—impossible to test all of them.
So he adopted statistician George Box's design of experiments method—testing only boundary combinations while keeping one parameter at its median value each time. With just 13 test prints, he established an initial model for top surface quality.
The scoring system ranged from 1 (delamination/failure) to 10 (comparable to ironing). Results showed that the region with low line width + low flow rate + medium speed performed best.

Taking It Further with Bayesian Optimization

He then introduced Bayesian optimization, allowing the algorithm to intelligently recommend new parameter combinations based on existing data, focusing the search on high-potential areas.
The optimal samples achieved top surface quality approaching ironing, while reducing print time by approximately 34%.

Reproducible Results, Open-Source Tools

These parameters were successfully verified by third parties (one outlier was due to incorrect flow rate settings on the printer in question). Meanwhile, the maker released a test model on Makerworld that reveals common top surface defects in just ten minutes of printing: transition lines, gaps, over/under-extrusion, delamination, and more.
Not relying on ironing, but on scientific parameter tuning—this is the path forward for true tech enthusiasts.






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