Purpose The purpose of this study is to evaluate the capability and performance of analytical models to predict the structural mechanical behaviour of parts fabricated by fused deposition modelling (FDM).… Click to show full abstract
Purpose The purpose of this study is to evaluate the capability and performance of analytical models to predict the structural mechanical behaviour of parts fabricated by fused deposition modelling (FDM). Design/methodology/approach A total of eight existing and newly proposed analytical models, tailored to satisfy the structural behaviour of FDM parts, are evaluated in terms of their capability to predict the ultimate tensile stress (UTS) and the elastic modulus (E) of parts made of polylactic acid (PLA) by the FDM process. This evaluation is made by comparing the structural properties predicted by these models with the experimental results obtained from tensile tests on FDM specimens fabricated with variable infill percentage, perimeter layers and build orientation. Findings Some analytical models are able to predict with high accuracy (prediction errors smaller than 5%) the structural behaviour of FDM and categories of similar additive manufactured parts. The most accurate model is Gibson’s and Ashby, followed by the efficiency model and the two new proposed exponential and variant Duckworth models. Research limitations/implications The study has been limited to uniaxial loading conditions along three different build orientations. Practical implications The structural properties of FDM parts can be predicted by analytical models based on the process parameters and material properties. Product engineers can use these models during the design for the additive manufacturing process. Originality/value Existing methods to estimate the structural properties of FDM parts are based on experimental tests; however, such methods are time-consuming and costly. In this work, the use of analytical models to predict the structural properties of FDM parts is proposed and evaluated.
               
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