As 3D printing technology becoming more mature and cheaper, it is commonly used in prototyping, production, and other scenarios. However, there is one limitation for the large object printing: print objects are limited by the printing space of 3D printers. To solve this problem, we can optimally separate the large 3D model and merge the partitions after printing the individual parts.
For the optimization of 3D model partitions, the initial design stage has a tremendous effect on the quality of 3D printed objects. With additive manufacturing (AM), the traditional process of fabrication is reversed. Objects are created by ‘adding’ material layer-by-layer, instead of through the traditional ‘subtractive’ methods. This means the sliced files uploaded to the printer need to be exactly as the designer intended. Otherwise, the print may fail or not accurately represent the designer’s intentions. These issues must be avoided at the initial design stage.
Partitioning Large Prints
Such a high standard of design inevitably creates multiple issues. One issue is the size of prints. Although the improving quality of FFF printers is making industrial-grade results more affordable, their small size may limit the dimensions of the final print.
The solution lies within the design phase. The print needs to be segmented using CAD, with each piece divided in a way that maximizes the available space within the printer. The following pictures showcase an example of how straight cuts would look on a 3D model, and how they could be connected.
The partitioning of an object can be achieved in many ways. The main aspects considered to make the optimization of the partition successful are:
- Printability- the parts must fit in the printer.
- Assemblability- it must be possible to easily put the parts together.
- Aesthetics- the seams should not be evident to the naked eye and should follow the natural symmetry of the final object.
Academics have tried to develop algorithms to help improve the designer’s ability to get the best result. One of the most mentioned works from the last decade addressing this issue is the automatic segmentation system called ‘Chopper’, developed in 2012 by Professor Luo Linjie from the Computer Science department at Princeton University.
The following picture shows an object that’s been partitioned using the ‘Chopper’ algorithm. The algorithm has additional requirements that seek to optimize the object’s printability and assembly sequence (pairing the two parts to be joined at each step).
The algorithm is based on Binary Space Partitioning (BSP). This means that when the object is being analyzed it will be evaluated by a series of conditions that must be met before being partitioned. It will continue evaluating the object and dividing pieces until it reaches an ‘optimum’ for that print.
These conditions are a series of objectives that are explored by the algorithm, which can either be automatic or set up by the user. These include:
- Several parts– estimation of the minimum number of prints possible to complete the object.
- Connector feasibility– maximization of the potential quality of connector placement and consequential object robustness.
- Structural soundness– avoidance of cuts through high-stress areas of the object.
- Fragility– avoidance of cuts in areas where the user does not want them for aesthetics (e.g. the face of a bust) and encouragement of symmetric cuts.
‘Chopper’ is limited by the partitioning options that the designer is willing to apply to their design. Meaning ‘Chopper’ isn’t always a viable choice for product design, but instead can be used to provide suggestions.
Partitioning Smaller Prints
Design issues are not only limited to size. Complex designs (like hollow or irregular shaped prints) can be printed by using temporary support structures. This is not a limit per se, but support structures require additional material cost, longer print times, and eventually more post-processing (time needed for removing support material). Partitioning can be an effective way of avoiding the downsides caused by using supports.
Digital partitioning algorithms are particularly useful for single objects. This is especially true when each section has a different surface material, and each piece needs to be easy to assemble. ‘Surface2Volume’ is an algorithm presented in a 2019 paper by Chrystiano Araùjo, a Ph.D. student in Computer Science from the British Columbia University of Vancouver. This algorithm was tested using multi-material, multicolor prints.
This algorithm addresses assemblability instead of printability. It can be difficult to partition an object with complex designs while still finding a feasible interlocking configuration. That’s why the algorithm is designed to find what the paper calls “as-assemblable-as-possible-partitioning”.
This means that an object’s shape is analyzed through a set of prioritized interlocking positions to choose where to put the best possible cut:
- Direction Initialization– Assesses the best extraction direction between two pieces (usually the user can choose from several possibilities).
- Discrete Partitioning– Prioritizes spots where extraction is possible and the structure is more robust.
- Interface Optimization– Enforces interface extractability for all feasible parts and smooths these interfaces to produce easier-to-manufacture parts.
The algorithm gets to a solution only when all designed parts are extractable.
Results achieved in this paper demonstrated that this method can work for both simple and complex designs, with extractable partitioning achieved within ten minutes. On the other hand, the researchers admitted that these results were obtained from a single material and that other materials may provide less impressive results. Besides, these experiments traded accuracy with the robustness of the design. Better results need a longer calculation time.
With the development of 3D printing technology, it takes a long time on post-processing when we print large-sized parts. Even though the algorithms have the limitations to be applied in slicing applications (like ideaMaker) and CAD now, it shows a good application prospect. The partitioning concept provides users a great concept on how to print large-scale products with the limited size of the 3D printer. Even though users now have to continue partitioning by hands, I believe they may be able to use automatic partitioning software soon. However, users will have to continue partitioning by hand until this software develops further.
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