## 1 Introduction
Although MEX is by far the most widespread form of AM technology, with 2.2 million printers sold in 2022 and an exponential growth rate forecasted [16], a significant barrier toward industrial usage is the uncertainty associated with part performance [14]. MEX polymers are classified as either commodity or high-performance, with the latter differentiated by a processing temperature above 250 \({}^{\circ}\)C [17]. High-performance materials are highly anisotropic [18; 19] and are yet to be validated for component production. This study instead focuses on the commodity polymer polylactic acid (PLA) since it is widely researched, and machines capable of producing PLA components are readily available. PLA is also less sensitive to variations in factors such as temperature and moisture, which enables a clearer evaluation of the variability in GD for AM component production. Traditional subtractive manufacturing techniques typically yield components with near isotropic material properties, making strength predictions straightforward. MEX components, however, are severely anisotropic both due to their porosity and inter-layer weaknesses, with a high likelihood that they will fail by delamination [14]. This characteristic is widely acknowledged and a common research topic; however, its effect on the adoption of GD is untouched. Every decision in the GD process impacts outcome performance. As the designer performs GD problem setup, they must choose from a range of (at face value) equally viable approaches when selecting objectives and constraints. Further variation is then introduced by the choice of tools with different solvers. Density methods such as SIMP produce radically different designs from a level-set algorithm. The selection here compounds variability upon the variability already inherent within the problem-framing stage. Post-generation, a further outcome performance range is introduced by subjectivity in the outcome evaluation process: decisions made about which GD outcome is most appropriate and how it should be post-processed introduce more sources of uncertainty. The strength of the design returned at the end of the entire GD process is, therefore, a function of every design decision made. Further variation is introduced into the process of physically realizing GD components in the AM process. MEX is a vastly complex procedure that is sensitive to variables that are directly controllable and uncontrollable by the user. As with the GD process, every decision made by an engineer utilizing MEX fixes the performance of their outcome in some way, from selecting the material with the'strongest color' to infill percentage. In particular, the largest variability is observed in the chosen AM build direction. Again, choices made regarding the post-processing of the printed design affect performance, with sanding and acetone rubbing leading to different strength defects. The overall GD for AM process is presented in Figure 1, with examples of design choices that would affect component performance shown at each stage. The contribution of this investigation lies in the identification of the variability of outcomes of GD components. The impact of this variability is evaluated in conjunction with the uncertainty in part performance associated with polymer MEX. To assess the range of possible outcomes produced in GD for AM, a structural problem was posed to nine groups of engineering designers, with the goal of maximizing the load that could be withstood before fracture through the use of Autodesk's Fusion 360 GD tool [20]. Besides some problem constraints, the designers were given complete freedom to set up the GD study and select their chosen outcome. The groups then simulated their designs to obtain an approximate gauge of their strength before producing them using AM in PLA. Finally, the AM components were loaded to failure, and the maximum load achieved was recorded for each design.