2026RESEARCH — MICROGRAVITY ADDITIVE MANUFACTURING

Vibration, answered in firmware

On a station, the micro-vibration environment shows up directly in the surface quality of an FDM print. Classical active vibration control answers that with another actuator. This work does not: it modulates the print head's instantaneous kinematic speed at the firmware level, so the motion itself avoids exciting the structure's resonances. To validate it on a bench I built the disturbance — a single-axis shaker rig, mechanics through desktop software.

77TH INTERNATIONAL ASTRONAUTICAL CONGRESS · ANTALYA · 5—9 OCTOBER 2026 · INTERACTIVE PRESENTATION · ROLE: RESEARCH IDEA, CONTROL DESIGN, TEST RIG

TAB 01IAC 2026 — THE STUDY

WHAT THE WORK LOOKS AT

  • How an ISS-like micro-vibration environment degrades FDM surface quality
  • An FxLMS-based control approach against that disturbance
  • A software answer instead of added hardware — no counter-actuator, no extra mass
  • Speed modulation as the control handle: resonances are avoided, not cancelled after the fact

MY CONTRIBUTION

  • The research idea, the experimental approach and the system concept
  • Design of the control side
  • Building the test rig the validation runs on
  • Paper title: Real-Time Active Vibration Compensation in Microgravity Additive Manufacturing via Kinematic Speed Modulation
TAB 02SINGLE-AXIS SHAKER RIG

1 kHz

POSITION SET-POINT UPDATE

±150 mm

USABLE STROKE

~10 kg

TARGET LOAD CLASS

<200 USD

COST, EXCL. PRINTER & PC

WHAT I BUILT

  • Mechanical layout and drive selection
  • STEP/DIR driver chain and power electronics
  • Firmware on an Arduino Nano
  • Python/Tk control application and the test logic around it

WHY IT EXISTS

  • The disturbance in the IAC study has to be physically reproducible to be argued about
  • One project carries mechanics, electronics, firmware, desktop software and test procedure
  • Open hardware — the whole rig is published, not described
  • github.com/dereyurtali/single-axis-shaker-rig
TAB 03PUBLICATIONS — IN PREPARATION

SURFACE ROUGHNESS · CUSP FILTERING

Effects of process parameters on surface roughness in fused deposition modelling after cusp filtering

ALI DEREYURT · EBUBEKIR KOÇ

Layer height, wall count, infill density and print speed studied in a full factorial design: 324 surface profiles collected from 108 specimens, measured to ISO 4287/4288. To separate out the dominant effect of layer geometry I developed a cusp filtering method locked to the measured peak and valley positions. After filtering, print speed becomes significant at p = 0.005.

108 specimens324 profilesISO 4287 / 4288p = 0.005

MULTI-OBJECTIVE OPTIMISATION

Multi-objective parameter optimisation in fused deposition modelling using machine learning and Bayesian optimisation

ALI DEREYURT · EBUBEKIR KOÇ

An end-to-end approach: the uploaded 3D model is read through four orthographic views and a vision-language model, roughness is predicted by monotonicity-constrained gradient boosting, and a Bayesian search balances roughness, material use, print time and structural strength — every candidate validated through the slicer. Shipped as a product at printimize.dereyurt.dev.

5-fold CV R² = 0.989 ± 0.007LOOCV R² = 0.991RMSE 0.569 µmfull cycle ≈ 270 s
TAB 04THE MANUFACTURING SIDE

3DOIT ADDITIVE MANUFACTURING

ENGINEER CANDIDATE · AUG 2024 — FEB 2025

FDM production management for aerospace and industrial prototyping: printer-farm operation, parameter optimisation, DfM, dimensional verification and surface inspection.

FSMVÜ ALUTEAM

PART-TIME STUDENT · OCT 2021 — FEB 2022

EOS SLS and DMLS systems: build preparation, powder handling, depowdering and surface finishing; 3D scanning and part inspection on a Hexagon robotic arm.