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Slic3r is free software 3D slicing engine for 3D printers. It generates G-code from 3D CAD files (STL or OBJ). Once finished, an appropriate G-code file for the production of the 3D modeled part, or object is sent to the 3D printer for the manufacturing of a physical object. As of 2013, about half of the 3D printers tested by Make Magazine supported Slic3r.
The analysis highlights Products and Art as prominent areas in the source structure around Slic3r.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Slic3r shows recurring relationship patterns in the source. For example, Slic3r → Archived, Github, Official, Wayback Machine Another extracted example is Slic3r → GNU AGPL. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
3d g-code prusaslicer printers fork slicing printer software website repository github cad free open-source portal engine generates files stl obj
TTTA extracted 11 structured relationships around Slic3r. Examples in this analysis include Slic3r → License → GNU AGPL and Slic3r → Operating system → Microsoft Windows, Mac OS X, Linux. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Slic3r | License | GNU AGPL | 1.00 | infobox |
| Slic3r | Operating system | Microsoft Windows, Mac OS X, Linux | 1.00 | infobox |
| Slic3r | Original author | Alessandro Ranellucci | 1.00 | infobox |
| Slic3r | Repository | github.com/slic3r/Slic3r | 1.00 | infobox |
| Slic3r | Stable release | 1.3.0 / May 10, 2018; 8 years ago (2018-05-10) | 1.00 | infobox |
| Slic3r | Type | 3D printer slicing application | 1.00 | infobox |
| Slic3r | Website | slic3r.org | 1.00 | infobox |
| Slic3r | related to External links | Official | 0.60 | section |
| Slic3r | related to External links | Github | 0.60 | section |
| Slic3r | related to External links | Archived | 0.60 | section |
| Slic3r | related to External links | Wayback Machine | 0.60 | section |
The concept neighborhoods around Slic3r bring nearby vocabulary together. In this analysis, examples include Printers, Slicing and Software. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Bridges highlight paths between different parts of the Slic3r map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Slic3r to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Products & Art, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Slic3r · EN edition · Analysis: TopicsToTalkAbout