Manufacturing Technology 2018, 18(3):372-378 | DOI: 10.21062/ujep/108.2018/a/1213-2489/MT/18/3/372

Optimizing Fabrication Outcome in Low-cost FDM Machines. Part 1 - Metrics

Francesco Buonamici, Monica Carfagni, Rocco Furferi, Lapo Governi, Marco Saccardi, Yary Volpe
Department of Industrial Engineering of Florence, University of Florence - Via di Santa Marta 3, 50139, Firenze, Italy

Several models of FDM machines, characterized by different architecture and hardware components, have flooded the market in the last 5 years. As a result, given the high sensitivity of FDM to the specific machine characteristics, the search for optimal printing parameters is a renown problem. This two-parts paper proposes an easy-to-follow and low-cost procedure for the characterization of any given FDM machine. The method allows the evaluation of the effects of a wide selection of FDM process parameters on the quality of 3D printed parts. The first part focuses on the definition of a series of metrics to be measured on a series of test prints to evaluate the quality of the produced parts. Specifically, several effects are considered: dimensional accuracy, small details, overhang surfaces, ability of printing small holes/thin extrusions and overall quality of the prints. The evaluation of seven quality parameters on a single print is made possible thanks to: i) a specifically designed specimen that is made available to the user and ii) a rigorous and repeatable measurement procedure, which are both discussed in the first part of the paper. The second part presents the characterization procedure, the statistical tools used in the experimentation and provides guidelines to be used for the characterization of any FDM machine. The whole procedure is tested on a desktop FDM machine to demonstrate obtainable results.

Keywords: Additive Manufacturing (AM), Fused Deposition Modeling (FDM), Process Optimization, Design of Experiments (DOE), 3D Printing

Published: June 1, 2018  Show citation

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Buonamici F, Carfagni M, Furferi R, Governi L, Saccardi M, Volpe Y. Optimizing Fabrication Outcome in Low-cost FDM Machines. Part 1 - Metrics. Manufacturing Technology. 2018;18(3):372-378. doi: 10.21062/ujep/108.2018/a/1213-2489/MT/18/3/372.
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    References

    1. CRUMP, S.S. (1992). Modeling apparatus for three-dimensional objects, 1992.
    2. PFEIFER, T., KOCH, C., VAN HULLE, L., CAPOTE, G.A.M., NATALIE, P. (2016). Optimization of the FDM Additive Manufacturing Process. In: 74th Annual Technical Conference and Exhibition of the Society of Plastics Engineers, pp. 22-29. Indianapolis.
    3. RAYEGANI, F., ONWUBOLU, G.C. (2014). Fused deposition modelling (fdm) process parameter prediction and optimization using group method for data handling (gmdh) and differential evolution (de). In: International Journal of Advanced Manufacturing Technology, Vol. 73, No. 1-4, pp. 509-519. Go to original source...
    4. CHRISTIYAN, K.G.J., CHANDRASEKHAR, U., VENKATESWARLU, K. (2016). A study on the influence of process parameters on the Mechanical Properties of 3D printed ABS composite. In: IOP Conference Series: Materials Science and Engineering, Vol. 114, No. 1, pp. 12109. Go to original source...
    5. MOHAMED, O.A., MASOOD, S.H., BHOWMIK, J.L. (2017). Experimental investigation of time-dependent mechanical properties of PC-ABS prototypes processed by FDM additive manufacturing process. In: Materials Letters, Vol. 193, pp. 58-62. Go to original source...
    6. WEINMANN, J., PRIGOZHIN, H. IP, D., ESCOBAR, E., MENDELSON, M., NOORANI, R. (2003). Applicaton of Design of Experiments (Doe) on the Processing of Rapid Prototyped Samples. In: Proceedings of The Solid Freeform Symposium, pp. 4-6. Austin, Texas.
    7. FERNANDEZ-VICENTE, M., CALLE, W., FERRANDIZ, S., CONEJERO, A. (2016). Effect of Infill Parameters on Tensile Mechanical Behavior in Desktop 3D Printing. In: 3D Printing and Additive Manufacturing, Vol. 3, No. 3, pp. 183-192. Go to original source...
    8. DOMINGO-ESPIN, M., BORROS, S., AGULLO, N., GARCIA-GRANADA, A.A., REYES, G. (2014). Influence of Building Parameters on the Dynamic Mechanical Properties of Polycarbonate Fused Deposition Modeling Parts. In: 3D Printing and Additive Manufacturing, Vol. 1, No. 2, pp. 70-77. Go to original source...
    9. LINDA, M., MÜLLER, M., CHOTÌBORSKÝ, R. (2014). Evaluation of mechanical properties of samples printed by FDM method. In: Manufacturing Technology, Vol. 14, No. 1, pp. 56-60. Go to original source...
    10. MOHAMED, O.A., MASOOD, S.H., BHOWMIK, J.L. (2016). Mathematical modeling and FDM process parameters optimization using response surface methodology based on Q-optimal design. In: Applied Mathematical Modelling, Vol. 40, No. 23-24, pp. 10052-10073. Go to original source...
    11. THRIMURTHULU, K., PANDEY, P.M., VENKATA REDDY, N. (2004). Optimum part deposition orientation in fused deposition modeling. In: International Journal of Machine Tools and Manufacture, Vol. 44, No. 6, pp. 585-594. Go to original source...
    12. KUMAR, G.P., REGALLA, S.P. (2011). Optimization of Support Material and Build Time in Fused Deposition Modeling (FDM). In: Applied Mechanics and Materials, Vol. 110-116, pp. 2245-2251. Go to original source...
    13. PENG, A., XIAO, X., YUE, R. (2014). Process parameter optimization for fused deposition modeling using response surface methodology combined with fuzzy inference system. In: The International Journal of Advanced Manufacturing Technology, Vol. 73, pp. 87-100. Go to original source...
    14. PANDA, B.N., SHANKHWAR, K., GARG, A., JIAN, Z. (2017). Performance evaluation of warping characteristic of fused deposition modelling process. In: International Journal of Advanced Manufacturing Technology, Vol. 88, No. 5-8, pp. 1799-1811. Go to original source...
    15. INGRASSIA, T., NIGRELLI, V., RICOTTA, V., TARTAMELLA, C. (2017). Process parameters influence in additive manufacturing. In: Advances on Mechanics, Design Engineering and Manufacturing. Lecture Notes in Mechanical Engineering, pp. 261-270. Go to original source...
    16. AKANDE, S.O. (2015). Dimensional Accuracy and Surface Finish Optimization of Fused Deposition Modelling Parts using Desirability Function Analysis. In: International Journal of Engineering Research & Technology (IJERT), Vol. 4, No. 4, pp. 196-202. Go to original source...
    17. GALANTUCCI, L.M., BODI, I., KACANI, J., LAVECCHIA, F. (2015). Analysis of Dimensional Performance for a 3D Open-source Printer Based on Fused Deposition Modeling Technique. In: Procedia CIRP, Vol. 28, pp. 82-87. Go to original source...
    18. KROTKỲ, J., HONZÍKOVÁ, J., MOC, P. (2016). Deformation of print PLA material depending on the temperature of reheating printing pad, In: Manufacturing Technology, Vol. 16, No. 1, pp. 136-140. Go to original source...
    19. Slic3r - G-code generator for 3D printers. [Online]. Available: http://slic3r.org/. [Accessed: 28-Apr-2017].
    20. BAUMANN, F., BUGDAYCI, H., GRUNERT, J., KELLER, F., ROLLER, D. (2016). Influence of slicing tools on quality of 3D printed parts, In: Computer-Aided Design and Applications, Vol. 13, No. 1, pp. 14-31. Go to original source...
    21. NANCHARAIAH, T., RAJU, D., RAJU, V. (2010). An experimental investigation on surface quality and dimensional accuracy of FDM components, In: International Journal on Emerging Technologies, Vol. 1, No. 2, pp. 106-111.
    22. TAGUCHI, G. (1986). Introduction to Quality Engineering: Designing Quality into Products and Processes. Asian Productivity Organization, 1986.
    23. FDM Test Model - Evaluation of multiple effects by frank_2288 - Thingiverse. [Online]. Available: https://www.thingiverse.com/thing:2762593. [Accessed: 22-Jan-2018].
    24. ROMER Absolute Arm with integrated scanner. [Online]. Available: http://www.hexagonmi.com/products/portable-measuring-arms/romer-absolute-arm-with-integrated-scanner. [Accessed: 25-Jan-2017].
    25. DI ANGELO, L., DI STEFANO, P., MARZOLA, A. (2017). Surface quality prediction in FDM additive manufacturing. In: The International Journal of Advanced Manufacturing Technology, Vol. 93, No. 9-12, pp. 3655-3662. Go to original source...

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