AON3D accelerates FFF printing via physics-based G-code optimization

AON3D introduces a software update addressing throughput in material-extrusion printing. At its core is a downstream, physics-based optimization of G-code that reportedly reduced print times in tests by up to 54 percent without visible compromises in part quality and performance. In one example, the software shortened a 24-hour job by 13 hours. Together with the qualification software Basis, which monitors parts in real time, AON3D aims to bring additive processes closer to conventional manufacturing cycle times.

Technically, the new Throughput Optimization Module models the rheological and thermal properties of the polymer being used and simulates heat build-up and dissipation along toolpaths. Based on this, the software adjusts deposition rates depending on geometry, accelerating in cooler zones and throttling before areas at risk of overheating. At the same time, the algorithm accounts for so-called melt-fracture limits to avoid surface artifacts, and controls the process such that weld strength between layers remains consistent.

“Until now, polymer physics have been left out of the slicing process, relying solely on trial-and-error tuning — a time-consuming process with variable outcomes. AON3D’s Multiphysics Process Optimization changes this, achieving deterministic outcomes and tying predictions to results”, said Adrian Miresan, AON3D VP Software Research.

The approach differs from common acceleration strategies that rely mainly on larger nozzles, global speed offsets, and increased extrusion temperatures. Such settings ignore local cooling conditions and part geometries and frequently lead to sagging, rough surfaces, or variable anisotropy due to fluctuating interlayer bond strength.

For production-oriented FFF applications, reproducible cycle time with stable mechanics is critical. Whether the reported time gains can be broadly achieved depends on material variants, build-chamber cooling, and machine dynamics. If results hold across different geometries, physics-based post-optimization offers a pragmatic lever to boost throughput without changing hardware.