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Integration of Fuzzy Logic with Response Surface Methodology for Predicting the Effect of Process Parameters on Build Time and Model Material Volume in FDM Process

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CAD/CAM, Robotics and Factories of the Future

Abstract

Fused Deposition Modelling (FDM) is a promising additive manufacturing (AM) technique used for various prototyping requirements where relatively cheap yet robust models are required. To improve FDM process effectiveness, appropriate process parameters selection is required for high productivity and cost effectiveness. Build time (BT) and volume of Model material (MMV) required are important responses to measure cost effectiveness. In this work, response surface methodology (RSM) and fuzzy logic (FL) have been applied to reduce the build time and model material volume for experimentation. The process parameters namely contour width, air gap; raster angle and spatial orientation are considered. Also, build time and model material volume has been taken as responses for this study. Thirty experiments were conducted on AcrylobutadieneStyrene (ABS) P400 for conical primitives using full factorial central composite RSM design. The optimum process parameter conditions were obtained from FL. The results obtained provide useful information of the method to control responses and ensure minimal build time and model material volume for prototyping requirements. The assessment outcome provided a scientific reference to obtain minimal values of build time and model material volume utilized, and it was found out that these correspond to a contour width of 0.654 mm, air gap of 0.0254 mm, raster angle of 0° and orientation (rotation about x-axis keeping z height minimum) of 30°.

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References

  • Ahn, S. H., Montero, M., Odell, D., Roundy, S., & Wright, P. K. (2002). Anisotropic material properties of fused deposition modelling ABS. Rapid Prototyping Journal, 8(4), 248–257.

    Article  Google Scholar 

  • Arghavani, J., Derenne, M., & Marchand, L. (2002). Prediction of gasket leakage rate and sealing performance through fuzzy logic. International Journal of Advanced Manufacturing Technology, 20, 612–620.

    Article  Google Scholar 

  • Chouksey, A. (2012). Study of parametric optimization of fused deposition modelling process using response surface methodology. Thesis, Mechanical Engineering Department, NITRourkela.

    Google Scholar 

  • Chua, C. K., Feng, C., Lee, C. W., & Ang, G. Q. (2005). Rapid investment casting: direct and indirect approaches via model maker II. International Journal of Advanced Manufacturing Technology, 25, 11–25.

    Google Scholar 

  • Gibson, I., Rosen, D. W., & Stucker, B. (2010). Additive manufacturing technologies: Rapid prototyping to direct digital manufacturing. New York: Springer.

    Google Scholar 

  • Karthikeyan, R., Jaiganesh, S., & Pai, B. C. (2002). Optimization of drilling characteristics for Al/SiCP composites using fuzzy/GA. Metals and Materials, 8(2), 163–168.

    Article  Google Scholar 

  • Kumar, B. S., & Baskar, N. (2013). Integration of fuzzy logic with response surface methodology for thrust force and surface roughness modeling of drilling on titanium alloy. International Journal of Advanced Manufacturing Technology, 65, 1501–1514.

    Article  Google Scholar 

  • Levy, G. N., Schindel, R., Kruth, J. P., & Leuven, K. U. (2003). Rapid manufacturing and rapid tooling with layer manufacturing (LM) technologies—State of the art and future perspectives. CIRP annals-Manufacturing Technology, 52(2), 589–609.

    Article  Google Scholar 

  • Pilipovic, A., Raos, P., & Šercer, M. (2009). Experimental analysis of properties of materials for rapid prototyping. International Journal of Advanced Manufacturing Technology, 40, 15–105.

    Article  Google Scholar 

  • Ross, T. J. (1995). Fuzzy logic with engineering applications. New York: McGraw-Hill Inc.

    Google Scholar 

  • Sood, A. K. (2011). Study on parametric optimization of fused deposition modelling (FDM) process. NIT Rourkela: Thesis Mechanical Engineering Department.

    Google Scholar 

  • Srivastava, M., Maheshwari, S., & Kundra, T. K. (2014). Virtual Modelling and simulation of functionally graded materials using FDM process. Materials Today, Elsevier Proceedings.

    Google Scholar 

  • Stratasys. (2014). StatEase, Design Expert, F.I.T. package, Editor.

    Google Scholar 

  • Tarng, Y. S., Yang, W. H., & Juang, S. C. (2000). The use of fuzzy logic in the Taguchi method for the optimization of the submerged arc welding. International Journal of Advanced Manufacturing Technology, 16, 688–694.

    Article  Google Scholar 

  • Thrimurthulu, K., Pandey, P. M., & Venkata, Reddy N. (2004). Optimum part deposition orientation in fused deposition modeling. International Journal of Machine Tools and Manufacture, 44, 585–594.

    Article  Google Scholar 

  • Tzeng, Y.-F., & Chen, F.-C. (2007). Multi-objective optmisation of high-speed electrical discharge machining process using Taguchi fuzzy-based approach. Materials and Design, 28, 1159–1168.

    Article  Google Scholar 

  • Upcraft, S., & Flectcher, R. (2003). The rapid prototyping technologies. Rapid Prototyping Journal, 23(4), 318–330.

    Google Scholar 

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Correspondence to Manu Srivastava .

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Srivastava, M., Maheshwari, S., Kundra, T.K., Yashaswi, R., Rathee, S. (2016). Integration of Fuzzy Logic with Response Surface Methodology for Predicting the Effect of Process Parameters on Build Time and Model Material Volume in FDM Process. In: Mandal, D.K., Syan, C.S. (eds) CAD/CAM, Robotics and Factories of the Future. Lecture Notes in Mechanical Engineering. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2740-3_20

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  • DOI: https://doi.org/10.1007/978-81-322-2740-3_20

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2738-0

  • Online ISBN: 978-81-322-2740-3

  • eBook Packages: EngineeringEngineering (R0)

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