Abstract
Additive manufacturing (AM) technologies such as fused deposition modeling (FDM) rely on the quality of manufactured products and the process capability. Currently, the dimensional accuracy and stability of any AM process is essential for ensuring that customer specifications are satisfied at the highest standard, and variations are controlled without significantly affecting the functioning of processes, machines, and product structures. This study aims to investigate the effects of FDM fabrication conditions on the dimensional accuracy of cylindrical parts. In this study, a new class of experimental design techniques for integrated second-order definitive screening design (DSD) and an artificial neural network (ANN) are proposed for designing experiments to evaluate and predict the effects of six important operating variables. By determining the optimum fabrication conditions to obtain better dimensional accuracies for cylindrical parts, the time consumption and number of complex experiments are reduced considerably in this study. The optimum fabrication conditions generated through a second-order DSD are verified with experimental measurements. The results indicate that the slice thickness, part print direction, and number of perimeters significantly affect the percentage of length difference, whereas the percentage of diameter difference is significantly affected by the raster-to-raster air gap, bead width, number of perimeters, and part print direction. Furthermore, the results demonstrate that a second-order DSD integrated with an ANN is a more attractive and promising methodology for AM applications.
Highlights
The use of additive manufacturing (AM), such as fused deposition modeling (FDM) technology, has increased significantly over the past few years [1,2,3]
This study aims to investigate the effects of FDM fabrication conditions on the dimensional accuracy of cylindrical parts
The results indicate that the slice thickness, part print direction, and & Omar Ahmed Mohamed omar.ahmed.mohamed@outlook.com
Summary
The use of additive manufacturing (AM), such as fused deposition modeling (FDM) technology, has increased significantly over the past few years [1,2,3]. Determining whether an AM process is appropriate for industry requires an understanding of the quality aspects of the technology in terms of productivity and dimensional accuracy. For an AM technology such as FDM, the quality and continuous improvement of the FDM process are crucial and must be evaluated systematically by validating and controlling the dimensional accuracy of systems. When an appropriate measurement procedure is used, the measurements of product quality and dimensional stability are accurate; the quality characteristics can be controlled and the dimensional variations in the FDM manufactured products can be minimized [6]. Industries are becoming increasingly concerned and aware of the quality of FDM owing to its widespread use and expect a higher level of product performance than before. Numerous factors contribute to these undesirable effects on the product quality
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