In this Week, I have Contributed in the understanding characteristics of My 3D Printer
In our Lab we have two Printers one is from Creality and another one is from Flash Forge
For more about Group AssignmentThe FlashForge Creator 3 Pro is a professional IDEX (Independent Dual Extruder) 3D printer, allowing dual-material and multi-color printing. It has a 300°C high-temperature extruder, enabling compatibility with a wide range of filaments like PLA, ABS, PETG, PC, and Nylon. The heated flexible build plate improves adhesion and makes print removal easy. With an enclosed chamber, it maintains stable temperatures for better print quality. The active leveling system ensures precise calibration. It features Wi-Fi, USB, and Ethernet connectivity for remote operation. It cost comes around Rs. 2L
| Feature | Specification |
|---|---|
| Printing Technology | Fused Filament Fabrication (FFF) |
| Build Volume | 300 x 250 x 200 mm |
| Layer Resolution | 0.05 - 0.4 mm |
| Nozzle Diameter | 0.4 mm (Standard) |
| Printing Speed | ≤ 150 mm/s |
| Filament Diameter | 1.75 mm |
| Extruder Type | Independent Dual Extruders (IDEX) |
| Compatible Materials | PLA, ABS, PETG, TPU, PVA, Nylon, Carbon Fiber |
| Heated Bed | Yes (Max Temp: 120°C) |
| Nozzle Temperature | Max 320°C |
| Enclosure | Fully enclosed for temperature stability |
| Connectivity | USB, Wi-Fi, Ethernet |
| Power Supply | 24V / 500W |
| Display | 4.3-inch Touchscreen |
| Supported File Formats | STL, OBJ, 3MF, G-code |
| Compatible Software | FlashPrint, Simplify3D, Cura |
| Weight | 40 kg |
The model was designed in Fusion 360. The objective was to create a hollow interconnected pipe structure that could demonstrate the advantages of additive manufacturing. The geometry contains internal connections and curved paths that would be difficult to manufacture using conventional subtractive processes.
Figure 1: Creating the initial sketch profile in Fusion 360.
Figure 2: Creating the circular profile for the sweep operation.
Figure 3: Generating the hollow pipe using the sweep feature.
Figure 4: Repeating the sweep operation in multiple directions.
Figure 5: Final rendered model with appearance modifications.
The object contains multiple interconnected internal channels and curved geometries. Manufacturing such a structure using conventional subtractive machining would require several setups and specialized tooling. Some internal features are inaccessible to cutting tools, making the geometry difficult or impossible to produce using traditional machining methods. Therefore, additive manufacturing is the most suitable fabrication process for this design.
After completing the CAD design, the STL file was imported into Creality Slicer 4.8.2. Slicing software converts the 3D model into machine-readable G-code and allows configuration of print settings such as layer height, infill, supports, and print speed.
Figure 6: Creality Slicer 4.8.2 software interface.
We selected the Creality Smart CR-10 Pro printer profile to match the build volume and machine specifications.
Figure 7: Importing the STL model into Creality Slicer.
Figure 8: Initial model placement.
Figure 9: Scaling the model.
Figure 10: Rotating the model.
Figure 11: Final orientation before slicing.
Figure 12: Layer and print settings.
Figure 13: Support generation settings.
Figure 14: Slicing preview.
Figure 15: Generating G-code.
Figure 16: Exporting the final G-code file.
The object was printed using PLA filament. The following parameters were configured before starting the print:
Figure 17: Printer setup and parameter verification.
Figure 18: Initial layer deposition.
Figure 19: Printing progress.
Figure 20: Completed printed object.
Figure 21: Final finished model.
As in our lab we don't have any 3D Scanner, so we have to use the app called KIRI Engine
Download KIRI Engine from Google Play Store
Figure 1: KIRI Engine application interface.
Figure 2: Creating a new scanning project.
Figure 3: Configuring scan settings.
Figure 4: Preparing the image capture workflow.
For the initial 3D scanning experiment, I used the KIRI Engine mobile application. The application uses photogrammetry techniques to reconstruct a three-dimensional model from a collection of photographs. Images are captured from multiple viewpoints around the object and then processed to generate a textured 3D mesh.
To create the model, approximately 50 images were captured while moving around the object. These images were uploaded to KIRI Engine, where they were aligned and processed automatically. The software identified common feature points between images and reconstructed the object's geometry.
Figure 5: Uploading captured photographs.
Figure 6: Processing images in KIRI Engine.
Figure 7: Generating the 3D mesh.
Figure 8: Initial reconstructed model.
Although the generated model successfully captured the overall shape of the object, some surface details and geometric features were not reconstructed accurately. This motivated me to explore an alternative workflow using Polycam to achieve a higher-quality scan result.
Although KIRI Engine successfully generated a 3D model from the captured images, the reconstructed mesh contained several imperfections and missing surface details. To improve the quality of the reconstruction, I decided to perform a second scanning experiment using Polycam, a mobile-based photogrammetry application.
This second iteration allowed me to compare different photogrammetry workflows and evaluate how different reconstruction algorithms affect the final model quality. For this experiment, I selected a small Shinchan toy and captured a new set of photographs from multiple viewpoints.
Polycam is a mobile 3D scanning and photogrammetry application available for Android and iOS devices. The software uses a collection of photographs captured from different viewpoints and reconstructs them into a textured 3D model. It supports exporting models in formats such as STL, OBJ, FBX, and GLTF, making it suitable for visualization, reverse engineering, and rapid prototyping workflows.
For this scanning experiment, I selected a small plastic Shinchan toy. The object contains curved surfaces, facial details, and geometric features that make it suitable for evaluating the performance of photogrammetry-based 3D reconstruction.
Using my smartphone, I captured multiple images while moving around the object from different angles. Photographs were taken from the front, rear, sides, and top views to ensure complete surface coverage. Maintaining sufficient overlap between images helped Polycam accurately identify common feature points and reconstruct the geometry.
After completing the image acquisition process, Polycam processed the collected photographs and automatically generated a textured 3D model. The software analyzed common feature points between images and reconstructed the geometry using photogrammetry algorithms.
Figure 3: Textured 3D model generated by Polycam and previewed directly on the mobile device.
The generated model was then reviewed directly on the mobile device. This allowed me to inspect the reconstructed mesh, verify the captured details, and evaluate the overall quality of the scan before exporting the final model.
Figure 3: Textured 3D model generated by Polycam and previewed directly on the mobile device.
Once satisfied with the reconstruction quality, I exported the generated model in GLTF format. The exported file preserves both geometry and texture information, making it suitable for further visualization and sharing.
To inspect the model interactively, I uploaded the exported file to Sketchfab. The online viewer allowed me to rotate, zoom, and examine the reconstructed model from different angles. Compared to the initial KIRI Engine scan, the Polycam-generated model demonstrated better texture quality, improved surface reconstruction, and more accurate geometry.
After performing the scan refinement process, KIRI Engine generated a significantly improved 3D model. The refinement stage reconstructed the geometry more accurately by analyzing additional image data and improving mesh generation. The final model preserved most of the object's surface details and overall shape, demonstrating the effectiveness of photogrammetry-based scanning using a smartphone.
The generated mesh was exported and uploaded to Polycam for visualization and sharing. The interactive viewer allows the model to be inspected from different angles and provides a better understanding of the reconstructed geometry.
Although the scan successfully captured the overall geometry, some minor surface imperfections and mesh artifacts were still visible. These limitations are common in photogrammetry workflows and can be reduced by increasing the number of input images, improving lighting conditions, and maintaining consistent camera positioning during image capture.
Compared to the initial KIRI Engine scan, the Polycam-generated model showed improved surface quality, better texture mapping, and more accurate geometric reconstruction. This exercise demonstrated how different photogrammetry tools can produce varying levels of detail depending on their reconstruction algorithms.
I can't able to export those STL files of Mouse and Shinchan Toy due to subscription restriction. Sorry :-(