Development of Rapid Tooling Using Fused Deposition Modeling

  • Kamaljit Singh Boparai
  • Rupinder Singh


This chapter highlights the in house development of low cost alternative FDM feedstock filament with tailor made properties. The experimental study was performed to fabricate (Nylon6-Al-Al2O3 based) alternative fused deposition modeling (FDM) feedstock filament in place of commercial acrylonitrile butadiene styrene (ABS) filament (having specific rheological and mechanical properties) for rapid manufacturing (RM) and rapid tooling (RT) applications. The detailed steps for fabrication of alternative FDM feedstock filament (as per field application) with relatively low manufacturing cost and tailor made properties have been highlighted. The rheological and mechanical suitability of Nylon6-Al-Al2O3 feedstock filament has been verified experimentally. The approach is to predict and incorporate essential properties such as flow rate, flexibility, stiffness, and mechanical strength at processing conditions and compared with commercial ABS material. The proportions of various constituents have been varied in order to modify and improve rheological behavior and mechanical properties of alternative FDM feedstock filament. The developed feed stock filament was loaded in commercial FDM setup without any change in hardware and software. The results of study suggest that the newly developed composite material filament has relatively poor mechanical properties but have high thermal stability and wear resistant as compared to ABS filament and hence can be used for tailor made applications.

Finally, the Taguchi experimental log have been designed for investigating the significance of input parameters of screw extruder (such as: mean barrel temperature, die temperature, screw speed, material composition and speed of take up unit) on the diameter deviation of fabricated filaments was analyzed. The tensile strength of alternative feedstock filament has been investigated experimentally according to ASTM-638 standard. The analysis was performed by ANOVA method with the help of MINITAB 17 software. The regression model was developed to realize the influence of input parameters on responses. Tensile strength was significantly affected by the variation of major input parameters during the processing of alternative material on single screw extruder. The ANOVA analysis shows that two process parameters (namely: material composition and die temperature) were significant and remaining two (mean barrel temperature and screw speed) were insignificant. Further a linear regression model has been developed to accurately predict the tensile strength and diameter deviation of alternative feed stock FDM filament. The results highlight that the deviation of <1% was observed in the nine sets of experimental runs, which were compared with predicted values of the regression model. The dynamic mechanical analysis (DMA) result indicates that the filament fabricated with optimum combination of parameters have highest stiffness and more suitable for FDM system. The process capability study suggest that, with optimum combination of single screw extruder parameters, the process lies within the spread of ±4σ having Cp and Cpk value 1.43 and 1.354 respectively. The cost effective solution investigated in this research work may help in enhancing the application of FDM process for various industrial applications.


Additive manufacturing Fused deposition modeling Acrylonitrile butadiene styrene Feedstock filament Composite material 


  1. 1.
    Singh R. Some investigations for small-sized product fabrication with FDM for plastic components. Rapid Prototyping Journal. 2013 Jan 11;19(1):58–63.CrossRefGoogle Scholar
  2. 2.
    Nikzad M, Masood SH, Sbarski I. Thermo-mechanical properties of a highly filled polymeric composites for fused deposition modeling. Materials & Design. 2011 Jun 30;32(6):3448–56.CrossRefGoogle Scholar
  3. 3.
    Singh Boparai K, Singh Boparai K, Singh R, Singh R, Singh H, Singh H. Experimental investigations for development of Nylon6-Al-Al2O3 alternative FDM filament. Rapid Prototyping Journal. 2016 Mar 21;22(2):217–24.CrossRefGoogle Scholar
  4. 4.
    Mostafa N, Syed HM, Igor S, Andrew G. A study of melt flow analysis of an ABS-Iron composite in fused deposition modelling process. Tsinghua Science & Technology. 2009 Jun 30;14:29–37.CrossRefGoogle Scholar
  5. 5.
    Masood SH, Song WQ. Development of new metal/polymer materials for rapid tooling using fused deposition modelling. Materials & design. 2004 Oct 31;25(7):587–94.CrossRefGoogle Scholar
  6. 6.
    Wang M, Wang W, Liu T, Zhang WD. Melt rheological properties of nylon 6/multi-walled carbon nanotube composites. Composites Science and Technology. 2008 Sep 30;68(12):2498–502.CrossRefGoogle Scholar
  7. 7.
    Shenoy AV, Saini DR, Nadkarni VM. Rheology of nylon 6 containing metal halides. Journal of Materials Science. 1983 Jul 1;18(7):2149–55.CrossRefGoogle Scholar
  8. 8.
    Ramanath, H.S., Chua, C.K., Leong, K.F. Melt flow behavior of poly-ɛ caprolactone in fused deposition modeling J Mater Sci: Mater Med .2008 19: 2541.Google Scholar
  9. 9.
    Bellini A, Shor L, Guceri SI. New developments in fused deposition modeling of ceramics. Rapid Prototyping Journal. 2005 Sep 1;11(4):214–20.CrossRefGoogle Scholar
  10. 10.
    Zhang Y, Chou YK. Three-dimensional finite element analysis simulations of the fused deposition modelling process. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 2006 Oct 1;220(10):1663–71.CrossRefGoogle Scholar
  11. 11.
    Bose S, Mahanwar PA. Effect of flyash on the mechanical, thermal, dielectric, rheological and morphological properties of filled nylon 6. Journal of Minerals & Materials Characterization & Engineering. 2004 Jan 1;3(2):65–89.CrossRefGoogle Scholar
  12. 12.
    Spierings AB, Herres N, Levy G. Influence of the particle size distribution on surface quality and mechanical properties in AM steel parts. Rapid Prototyping Journal. 2011 Apr 26;17(3):195–202.CrossRefGoogle Scholar
  13. 13.
    Luyt AS, Molefi JA, Krump H. Thermal, mechanical and electrical properties of copper powder filled low-density and linear low-density polyethylene composites. Polymer Degradation and Stability. 2006 Jul 31;91(7):1629–36.CrossRefGoogle Scholar
  14. 14.
    Benmesli S, Riahi F. Dynamic mechanical and thermal properties of a chemically modified polypropylene/natural rubber thermoplastic elastomer blend. Polymer Testing. 2014 Jun 30;36:54–61.CrossRefGoogle Scholar
  15. 15.
    Sawpan MA, Holdsworth PG, Renshaw P. Glass transitions of hygrothermal aged pultruded glass fibre reinforced polymer rebar by dynamic mechanical thermal analysis. Materials & Design. 2012 Dec 31;42:272–8.CrossRefGoogle Scholar
  16. 16.
    Qiao J, Amirkhizi AV, Schaaf K, Nemat-Nasser S. Dynamic mechanical analysis of fly ash filled polyurea elastomer. Journal of Engineering Materials and Technology. 2011 Jan 1;133(1):011016.CrossRefGoogle Scholar
  17. 17.
    Shanmugam D, Thiruchitrambalam M. Influence of alkali treatment and layering pattern on the tensile and flexural properties of Palmyra palm leaf stalk fiber (PPLSF)/jute fiber polyester hybrid composites. Composite Interfaces. 2014 Jan 2;21(1):3–12.CrossRefGoogle Scholar
  18. 18.
    Rajesh C (2007) Development and characterization of Nylon Fiber Reinforced NBR composites. Thesis, Department of Chemistry, University of Calicut.Google Scholar
  19. 19.
    Murayama T (1999) Dynamic Mechanical Analysis of Polymeric Materials. Elsevier, New York.Google Scholar
  20. 20.
    Arora HS, Singh H, Dhindaw BK. Some observations on microstructural changes in a Mg-based AE42 alloy subjected to friction stir processing. Metallurgical and Materials Transactions B. 2012 Feb 1;43(1):92–108.CrossRefGoogle Scholar
  21. 21.
    Jayaraman M, Sivasubramanian R, Balasubramanian V, Lakshminarayanan AK. Optimization of process parameters for friction stir welding of cast aluminium alloy A319 by Taguchi method.Google Scholar
  22. 22.
    Tamizharasan T, Kumar S. Optimization of cutting insert geometry using DEFORM-3 D: numerical simulation and experimental validation. International Journal of Simulation Modelling. 2012 Jun 1;11(2):65–76.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Kamaljit Singh Boparai
    • 1
  • Rupinder Singh
    • 2
  1. 1.MRS Punjab Technical University BathindaBathindaIndia
  2. 2.Guru Nanak Dev Engineering College LudhianaLudhianaIndia

Personalised recommendations