Prediction and Improvement of warpage in parts fabricated using material extrusion process /
Muhammad Sufyan
- 80p. Soft Copy 30cm
Additive Manufacturing (AM) has transformed manufacturing by enabling the fabrication of complicated geometries with less material waste which is particularly beneficial in a variety of industries, including aerospace, automotive, healthcare, and consumer goods. Fused Deposition Modeling (FDM) is a prominent approach in the realm of AM, attributed to its economic practicality, user-friendly execution, and material flexibility. The persistent of warpage in FDM poses a critical challenge in FDM affecting dimensional accuracy, fitment and mechanical reliability of components. Despite advancements, a lack of comprehensive studies on the combined effects of key process parameters limits the ability to predict and mitigate the effect of warpage. This research aims at providing approaches to rectify warpage in FDM-printed parts a priority based on process improvements. This research investigates three critical printing parameters i.e., raster pattern, bed temperature, and infill density. Samples are printed with various printing conditions and warpage is measured followed by validation using FEA analysis. The initially developed predictive model gained relatively high precision with overall variance of value being less than 10% in accordance with experimental tests. FEA simulations show that the FCC raster pattern decreases warping by 40% than the grid raster pattern. Similarly, 80ºC bed temperature decreases warpage by 30% comparing with 40ºC. Infill density of 90% decreases warpage by 20% more than 10% infill density. Optimizing key process parameters in FDM can significantly reduce warpage, improving dimensional accuracy and mechanical reliability in precision-critical applications.