# On the Impact of Additive Manufacturing Processes Complexity on Modelling
This way, all the classifications of benefits and challenges (i.e., 4 Ms and 3m's, above) can be integrated in terms of specific components' features. It is noted that the main focus of this work is on variables involved, thus the listofModels is the most related term. As proven in literature, there are many attempts to correlate quality issues in particular with modelling aspects, throughout the entirety of the AM processes. For instance, in metal-AM processes and especially on powder bed fusion processes, the investigation of process parameters (input variables--tuned) on the performance indicators (output variables--regulated) depending on the scale of the modelling. Primarily, four multi-scale modelling techniques occur in the literature [41; 42; 43], (i) the micro-scale which focuses on the discrete powder level and examine the melt-pool dynamics, (ii) the meso-scale which focuses on continuous powder and study the thermal-field and the melt-pool dimensions, (iii) the macro-scale which aims on the building low volume geometries and investigates the developed thermal- and stress-field and (iv) the part-scale which does not consider a moving printing head, but the heating of upper nodes in equivalent layers (namely flash heating method). An analytical model for the thermal field is constructed by the authors of [44] to predict the quality aspect of density of printed parts, producing the process map of two different alloy materials. Similar to metallic-AM one, the first three scales come upon to SLA [45]. Nevertheless, each one targets different phenomena. For instance,  
Figure 1: Issues in AM (adapted from [18]). the micro-scale of SLA investigates the chemical, thermal and mechanical behavior of resin and the meso-scale focuses on the cured-depth. The macro-scale in both SLM and SLA, explore the thermal expansion of the printing body. An approach to determine the optimal orientation of SLA-fabricated parts is investigated by [46] utilizing parametric finite element method simulations to identify the minimum deformations. In AM for construction purposes such as cement-based AM, mechanical and rheological have to be assessed for adequate bond strength between the layers [47]. A study on 3D-printing of concrete is conducted by [48] to predict the quality aspect of cross-section in matter of layer height and width through computational fluid dynamics (CFD), validating it with experimental results. FDM is another AM process that requires the attention to the quality challenges. In the literature, the authors of [49] consider the adoption of FEA modelling to predict the structural behavior of two test cases. As such, it can be claimed that the complexity introduced by processes mechanism (and consequently by processes modelling) in design and operation phases is quite differentiated among the various processes. From the point of view of standard process planning procedure [50] two major factors are utilized in a process family selection; material properties and production rate (or volumes) [1]. The family of additive manufacturing, however, is pretty much well defined in such a space of two variables; almost all materials are addressed and it regards rather customization, i.e., not high production volumes. To this end, one would need further criteria to proceed with the exact AM selection [51; 52]. Also, at the same time, during both the design and operation phases of manufacturing, it is highly desirable to have criteria for modelling the process [53; 54] also towards digital twins' inclusion [55]. To this end one would need similar criteria with respect to the process, and potentially the machine [56]. It seems that process mechanism could be described by temperature [57; 58; 59] and the product could be represented by its size [60; 61]. However, the modelling is not included yet as an aspect.