Computer aided decision support for fused deposition modeling

Abstract

Parts formed using fused deposition modeling (FDM) can vary significantly in quality depending on the manufacturing process plan. Altering the plan profoundly affects the character of the resulting part. Although the designer and the machine user may have preferences regarding the part build and the relative importance of build outcomes such as production speed, dimensional accuracy, and surface quality, setting process variables to ensure desired results is a complex task. A multi‐objective decision support system has been developed to aid the user in setting FDM process variables in order to best achieve specific build goals and desired part characteristics. The method uses experimentation to quantify the effects of FDM process variables on part build goals, and to predict build outcomes and expected part quality. The system offers the user the ability to quantify the trade‐offs among conflicting goals while striving towards the best compromise solution.

Development of a design feature database to support design for additive manufacturing

“…Within the CAO software, the soft kill option (removing non-efficient material) and finite element analysis analysis of the model were performed so as to obtain an optimal design. Other technical aids include those proposed by Ziemian and Crawn (2001) who developed a decision support tool for Fused Deposition Modelling systems to guide users for the most optimal build settings. Pandey et al (2007) suggested that part deposition orientation is a major factor for AM as it effects build time, support structure, dimensional accuracy, surface finish and cost of the end product.…”

Multi-criteria selection of structural adhesives to bond ABS parts obtained by rapid prototyping

“…Therefore, in the recent years several research works have been published (e.g., [5][6][7][8]) for improving specific attributes of parts obtained by FDM such as surface finishing or dimensional accuracy. These works modify characteristic parameters of the process, such as the thickness of each layer, orientation of the piece or structure of filling material.…”

Application of taguchi experimental design for identication of factors influence over 3D printing time with fused deposition modeling

“…On the contrary, the use of the term "Fused Deposition Modeling" is found with greater relevance in quantity as well as in the number of quotes, for example, we see that [15], [16] refers with this term to a study of Surface finishing vs deposition time of melted material, [17] refers to it for a study of mechanical featuring of manufactured parts using this technology, [18], [19] in research for the use of polymethylmethacrylate through 3D printing for the manufacture of implants using FDM technology, and [20] develops a support system of multiobjective decisions to assist users of FDM processes to select the setting variables to achieve specific targets in regard to the characteristics of the parts of the piece to be printed. Finally, referencing the technology like "Fused deposition modeling" for the design and construction of a 3D printer [21], [22].…”