Achievements and results
Tool Changer from E3D.
One of the prototypes developed by the Université Centrale Lille and CNRS.
Made at the end of 2020, this is a versatile development machine on which we were able to develop an extrusion system with charged polymer granules (stainless steel, ceramic, etc.). We can therefore use materials on the market at lower cost and more accessible with more technical materials. We can thus use the printing system to its full capacity, change the materials but also the tools
We started with the Archimedean screw extrusion system developed by the company MAOR. The system has been optimised to avoid clogging of the screw by increasing the cooling of the pellets before the extrusion system.
Pirox furnace for thermal sintering after printing. Centrale Lille in partnership with CNRS and CRITT MDTS are developing a low-cost sintering strategy (sintering under RH5 gas or vacuum).
- 1st part: sintering under dihydrogen gas
- 2nd part: under vacuum
- 3rd part: sintering under RH5
Industrial 3D machine
Industrial 3D machine developed by the company Poelen which allows 3D printing for granule extrusion
Industrial 3D printer Admaflex 130
Resin printing machine which allows to print a resin loaded with technical materials. After debinding and sintering, this process results in metallic or ceramic parts.
Stainless steel 316L
316L stainless steel part ready to be sintered inside the Pirox furnace.
Example of a 316L stainless steel part sintered under dihydrogen.
Numerical simulation of the process and material characterisation
The detailed description of the additive manufacturing process by experimental means alone could become totally unaffordable due to the high cost in both human and material resources. Such a complex process can be modelled in terms of partial differential equations which, due to their complexity as non-uniform geometries, heterogeneity and non-linearity of the materials, and complex boundary conditions, cannot be solved in exact form and it is for this reason that numerical approximations remain how an appropriate, if not the only, strategy to tackle them, which in turn requires the use of intensive computing power.
This is precisely the case that (i) numerical modelling and (ii) high performance computing are two of Cenaero’s core competences. Indeed, within the framework of this project, a sintering model has been implemented using the finite element method with a pressure-velocity formulation that allows the treatment of large deformations. This is a specifically developed and well refined implementation with, among other things, two noteworthy features (i) the material parameters depend on the local density and (ii) such density evolution is related to the permanent mechanical deformation. These features establish the link between the thermodynamics and mechanics of the physical phenomena in question
A numerical model has already been well tested and validated. In addition and during this validation, a thorough investigation of the appropriate material parameters to be used in the numerical calculations was carried out. It was found that, in general, the current implementation gives very satisfactory results. However, several niches of opportunity for improvement and refinement were identified.
In order to further identify and prioritise the above improvements and refinements, a detailed study of the influence of material parameters on the sintering model was prepared, conducted and analysed. A brief description of its general methodology, some remarkable results and the general conclusions of the study will be outlined in the following.
Since (a) the variables with the most important impact on the mechanical performance of the finished part are (i) the density distribution and (ii) the mechanical contraction during the sintering process, and (b) both can be accurately obtained as output variables from the already available numerical implementation, the material input parameters, i.e. eleven thermal or mechanical variables, are increased and decreased respectively in the order of 1%, 2%, 4%, 8%, 16%, 32% and 64%, The material input parameters, eleven thermal or mechanical variables, are increased and decreased respectively by 1%, 2%, 4%, 8%, 16%, 32% and 64% in order to detail their respective influence on the final part.
Figure 1 shows the typical responses of the output variables, i.e. density (left) and shrinkage (right), in these cases when varying the transition temperature (top) and grain temperature (bottom). Next to these responses, the base case (red line), which most closely resembles the reference case (magenta line), is also displayed for comparison. It is important to note that in all cases the base and reference cases do not match perfectly, even though the reference case is almost always within the spam covered by the various responses. This fact reinforces the validation of the available numerical implementation and fulfils one of the main objectives of the work described here.