The digital transformation of manufacturing today is also occurring through new technological paradigms, such as additive manufacturing (AM), with numerous benefits, including a reduction in material waste compared to traditional production methods and lower energy consumption, which helps to improve the sustainability of the processes.
However, the AM process itself produces processing waste, which can be minimised through appropriate optimisation algorithms, developed through the use of mathematical models.
What is additive manufacturing?
Additive manufacturing is a term used to refer to 3D printing, namely, a process by which an object is manufactured starting from a digital file that represents a 3D model of the object, developed on a computer using modelling software or captured using a 3D scanner. This model is then physically created by the 3D printer by depositing successive layers of the chosen material with great precision, guided by the software, until the object is completed.
With the 3D printing technique, objects with very complex shapes can be manufactured, such as dental or orthopaedic prostheses.
Additive manufacturing: reducing waste as a key benefit
In addition to reducing the time required for prototyping, production, testing, and product placement on the market, by manufacturing the object through a single printing process requiring no moulds or specific equipment and tools, additive manufacturing allows a reduction in processing waste, which is normally a considerable expense for the company, affecting total production and disposal costs.
Creating the objects layer by layer with the additive manufacturing technique allows a reduction in costs and material waste of up to 90% .
 Sources: US Department of Energy – Energy Efficiency & Renewable Energy; Journal of Manufacturing and Materials processing; CMCT – California’s Manufacturing Network;
In traditional manufacturing methods and processes based on turning and milling, the final product is smaller than the initial block from which it was obtained through the progressive removal of material. In addition, the removed material, consisting of chips or shavings, is not easily reusable and must be disposed of as waste or reprocessed to make it usable.
Waste in additive manufacturing: an ongoing challenge
Although it allows greater freedom, design efficiency and material savings than traditional manufacturing methods, the additive manufacturing process itself is open to improvement.
The creation of additional support structures is often required, especially when printing complex geometries. For example, to support protruding parts of the object or undercuts during the manufacturing process and prevent them from deforming or collapsing due to the effect of gravity.
These supports can also help to mitigate the effects produced by thermal gradients, which form, for example, when the heat flow produced by the laser beam during printing of a metal object has to be channelled to accelerate the cooling of the object, and at the same time reduce the problems caused by the shrinkage of the material after solidification.
As mentioned, support structures are necessary for manufacturing objects with the AM technique, but they have several disadvantages: once the printing process is finished, they have to be removed, requiring additional time and work. Moreover, here too, the removed supports are wasted raw material as they cannot be reused. In addition, each time a support structure is added to the object being made, the printing time increases, together with the energy required, depending on the amount of supports needed and the volume of material.
Optimisation algorithms to reduce waste in AM
To solve these problems, mathematical models can be formed to develop specific algorithms to optimise the construction of the support structures in each particular case. On the one hand, the printer head paths can be optimised to reduce times and improve the quality of the deposition process. On the other, topological optimisation models can be developed. The idea behind topology optimisation is to go beyond classic shape optimisation and address the problem of material distribution, with the aim of minimising the necessary material while ensuring that the mechanical specifications of the piece are met. This type of algorithm is well suited for automatically calculating the optimal distribution of material inside the piece and for defining where the support structures are needed and what shape they should have to minimise waste.
The development of increasingly refined mathematical models and optimisation algorithms is reflected in the possibility to obtain higher quality 3D prints that reduce material waste, require less energy for their production and improve the sustainability of the manufacturing process.
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