Integration of CAD-guided automated insert placement for enhanced 3D printed component assembly

The paper presents an automated system for embedding brass threaded inserts into 3D-printed parts, reducing the variability of manual methods (misalignment, insufficient heating, excessive force) and the limitations of directly printed small threads (M4 and below). Target applications include rapid prototyping, low-volume production, and functional parts in aerospace and automotive sectors, where reliable joints enable repeated assembly. The device reads insert coordinates from Onshape (Parametric cloud CAD) via mate connectors (custom orientation systems in Onshape), ensuring faithful design-to-execution transfer. Its kinematics use a compact H-structure with a single-belt XY stage driven by stepper motors, plus a four-screw Z axis for uniform vertical motion and high stiffness. Inserts are automatically fed from a gravity tube through a servo-actuated lever and separator, then embedded with a heated tool head monitored by a thermocouple—tuned to 225 °C for PLA and 265 °C for ABS. A capacitive touch sensor provides real-time depth control (6 mm for M3, 8 mm for M4), while an inverted vise secures the workpiece above the tool head for optimal access. Integrating CAD data with Python motion-control scripts yields a low-operator workflow that improves repeatability and scalability. Tests on 3D printed parts of PLA and ABS with 3 to 6 perimeters show positional accuracy of ±0.05–0.07 mm, cycle times of 3.8–4.6 s per insert, and repeatability with 0.025–0.035 mm standard deviation—improving efficiency over manual methods by 73–75%. Thanks to modular design, compatibility with standard CAD platforms, and potential for adaptive tool heads, the system is well-suited for integration into automated additive-manufacturing post-processing lines and broader industrial adoption.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.18713313
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integration of CAD-guided automated insert placement for enhanced 3D printed component assembly

Florina Chiscop, Carmen-Cristiana Cazacu, Mihail Hanga, Dragos-Alexandru Cazacu et al.
Zenodo (CERN European Organization for Nuclear Research)
Manufacturing Process and Optimization
article

Integration of CAD-guided automated insert placement for enhanced 3D printed component assembly

Florina Chiscop, Carmen-Cristiana Cazacu, Mihail Hanga, Dragos-Alexandru Cazacu, Teodor-Cristian NAȘU
article en

Abstract

The paper presents an automated system for embedding brass threaded inserts into 3D-printed parts, reducing the variability of manual methods (misalignment, insufficient heating, excessive force) and the limitations of directly printed small threads (M4 and below). Target applications include rapid prototyping, low-volume production, and functional parts in aerospace and automotive sectors, where reliable joints enable repeated assembly. The device reads insert coordinates from Onshape (Parametric cloud CAD) via mate connectors (custom orientation systems in Onshape), ensuring faithful design-to-execution transfer. Its kinematics use a compact H-structure with a single-belt XY stage driven by stepper motors, plus a four-screw Z axis for uniform vertical motion and high stiffness. Inserts are automatically fed from a gravity tube through a servo-actuated lever and separator, then embedded with a heated tool head monitored by a thermocouple—tuned to 225 °C for PLA and 265 °C for ABS. A capacitive touch sensor provides real-time depth control (6 mm for M3, 8 mm for M4), while an inverted vise secures the workpiece above the tool head for optimal access. Integrating CAD data with Python motion-control scripts yields a low-operator workflow that improves repeatability and scalability. Tests on 3D printed parts of PLA and ABS with 3 to 6 perimeters show positional accuracy of ±0.05–0.07 mm, cycle times of 3.8–4.6 s per insert, and repeatability with 0.025–0.035 mm standard deviation—improving efficiency over manual methods by 73–75%. Thanks to modular design, compatibility with standard CAD platforms, and potential for adaptive tool heads, the system is well-suited for integration into automated additive-manufacturing post-processing lines and broader industrial adoption.

Zenodo (CERN European Organization for Nuclear Research)
University of Science and Technology (YE), National University of Science and Technology (ZW), Research Centre for Eastern and South Eastern Europe (DE), Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Industry, innovation and infrastructure
Openalex Percentile: Top 26%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.