Abstract
We present a heuristic procedure for determining key processing parameters (PPs) in materials-extrusion-based additive manufacturing processes. The concept relies on a design-of-experiment approach and consists of eleven “test objects” to determine the optimal combinations of key PPs values, starting with the PPs for printing the first layer and progressing to more complex geometric features, e.g., “bridges”. In each of the test objects, several combinations of the known PPs’ values are used, and only the values resulting in the best printed-part quality are selected for the following tests. The concept is intrinsically insensitive to different artefacts of the additive manufacturing machine (e.g., discrepancies between the nominal and actual nozzle diameters, and improper calibration of the feeding screws) and the optimal values of key PPs for manufacturing defect-free parts under the actual processing conditions can be determined. We validated the proposed procedure for two common commercial polymer feedstock materials, and we show that, by using the proposed procedure, it is possible to reduce the optimization time down to several hours, as well as to reduce the amount of consumed feedstock material. Tensile tests revealed a strong effect of amorphous and semi-crystalline nature of the polymer on the results of optimization. To the best of our knowledge, this is the first attempt to describe a systematic approach for optimizing PPs for materials extrusion-based additive manufacturing processes without relying on statistical data analysis or virtual simulations. The concept was implemented as a web-tool 3DOptimizer®.
Highlights
Additive manufacturing (AM) is no longer used to produce only prototypes, but it is slowly being established as a serial production method in the automotive, aerospace, medical, and sports industries [1,2]
This paper presents and experimentally validates a practical method that allows finding the process parameters (PPs)’ values for processing feedstock materials, using open-materials material-extrusion-based AM (MEAM) printers
If one uses the validated PP values, serious build defects will be naturally eliminated in the parts manufactured by MEAM
Summary
Additive manufacturing (AM) is no longer used to produce only prototypes, but it is slowly being established as a serial production method in the automotive, aerospace, medical, and sports industries [1,2]. (iii) material-specific parameters (rheological properties, thermal properties, (thermo-)mechanical properties, nature of the polymer, etc.), and (iv) geometry- and toolpath-specific parameters (number of perimeters, raster angle, infill percentage, infill type, support structures, etc.). Some of these quantities are often interdependent, and the above classification cannot be considered ultimate. The lack of general standards complicates meaningful comparisons between AM machines, feedstock materials, and final properties of MEAM parts This results in a situation in which AM engineers have to arrive at the optimal PPs’. This paper presents and experimentally validates a practical method that allows finding the PPs’ values for processing feedstock materials, using open-materials MEAM printers. To the best of our knowledge, this is the very first attempt to describe a simple systematic approach for optimizing key PPs in MEAM processes, without relying on statistical models or computationally costly simulations
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