Manufacturing Technology Today

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Analysis of Dimensional Variation in Fused Deposition Modeling Based 3d Printing Process Parameters for Better Dimensional Control


Affiliations
1 D. Y. Patil College of Engineering and Technology, Kasaba Bawada, Kolhapur, India
     

   Subscribe/Renew Journal


Additive Manufacturing (AM) is most promising technology in today’s manufacturing scenario. This technology is also known as 3D printing. Additive manufacturing construct the components by adding the material layer by layer. With advancement in technology additive manufacturing finds its application in almost every manufacturing sector and can build components of metal, polymers and composites. It offers huge design freedom and manufacture intricate shapes and parts of complex designs. This paper presents analysis of process parameters of Fused Deposition Modeling (FDM) for better dimensional accuracy. Different process parameters of FDM such as layer thickness, infill percentage and printing speed are considered for analysis. It is observed during this analysis that percentage variation of printed part inside diameter compared to that of 3D model inner diameter varied from 1.52% to 3.9%. Whereas percentage variation of square side of the printed part when compared with 3D model square side varied from 1.01% to 2.83%.

Keywords

Additive Manufacturing, 3D Printing, Fused Deposition Modeling, Surface Roughness, Optimization.
User
Subscription Login to verify subscription
Notifications
Font Size

  • Chinmay V. Sutar, Adish A. Mandavkar, Sairaj B Patil, Tejas U. Mohite, Tushar A. Patole, & Raykar, S. (2022). Analysis and prediction of working range of process parameters for surface roughness of 3D printed parts with fused deposition modelling. Journal of Manufacturing Engineering, 17(2), 044–050. https://doi.org/10.37255/jme.v17i2pp044-050

  • D’Addona, D. M., Raykar, S. J., Singh, D., & Kramar, D. (2021). Multi objective optimization of fused deposition modeling process parameters with desirability function. Procedia CIRP, 99, 707-710.

  • Deomore, S. A., & Raykar, S. J. (2021). Multi-criteria decision making paradigm for selection of best printing parameters of fused deposition modeling. Materials Today: Proceedings, 44, 2562-2565.

  • Jin, Y. A., He, Y., Fu, J. Z., Gan, W. F., & Lin, Z. W. (2014). Optimization of tool-path generation for material extrusion-based additive manufacturing technology. Additive Manufacturing, 1, 32-47.

  • Manglam, M. K., Rout, S. N., Kumari, S., Kumar, S., & Kar, M. (2022). Structural, magnetic and optical properties of (0.45) Ni0. 5Zn0. 5Fe2O4+(0.55) BaFe12O19 composite. Materials Today: Proceedings, 57, 418-421.

  • Patil, P., Raykar, S. J., Bhamu, J., & Singh, D. (2022). Modelling and analysis of surface roughness in fused deposition modeling based on infill patterns. Indian Journal of Engineering and Materials Sciences (IJEMS), 29(1), 92-99.

  • Raykar, S. J., & D’Addona, D. M. (2020). Selection of best printing parameters of fused deposition modeling using VIKOR. Materials Today: Proceedings, 27, 344-347.

  • Raykar, S. J., Narke, M. M., Desai, S. B., & Warke, S. S. (2020). Manufacturing of 3D printed sports helmet. In Techno-Societal 2018 (pp. 771-778). Springer, Cham.

  • Sood, A. K., Ohdar, R. K., & Mahapatra, S. S. (2009). Improving dimensional accuracy of fused deposition modelling processed part using grey Taguchi method. Materials & Design, 30(10), 4243-4252.

  • Wang, C. C., Lin, T., & Hu, S. (2007). Optimizing the rapid prototyping process by integrating the Taguchi method with the Gray relational analysis. Rapid Prototyping Journal, 13, 304-315.


Abstract Views: 70

PDF Views: 0




  • Analysis of Dimensional Variation in Fused Deposition Modeling Based 3d Printing Process Parameters for Better Dimensional Control

Abstract Views: 70  |  PDF Views: 0

Authors

Pratik E. Patil
D. Y. Patil College of Engineering and Technology, Kasaba Bawada, Kolhapur, India
Parth V. Patil
D. Y. Patil College of Engineering and Technology, Kasaba Bawada, Kolhapur, India
Sairaj B. Patil
D. Y. Patil College of Engineering and Technology, Kasaba Bawada, Kolhapur, India
Shivam S. Dhere
D. Y. Patil College of Engineering and Technology, Kasaba Bawada, Kolhapur, India
Sunil J. Raykar
D. Y. Patil College of Engineering and Technology, Kasaba Bawada, Kolhapur, India

Abstract


Additive Manufacturing (AM) is most promising technology in today’s manufacturing scenario. This technology is also known as 3D printing. Additive manufacturing construct the components by adding the material layer by layer. With advancement in technology additive manufacturing finds its application in almost every manufacturing sector and can build components of metal, polymers and composites. It offers huge design freedom and manufacture intricate shapes and parts of complex designs. This paper presents analysis of process parameters of Fused Deposition Modeling (FDM) for better dimensional accuracy. Different process parameters of FDM such as layer thickness, infill percentage and printing speed are considered for analysis. It is observed during this analysis that percentage variation of printed part inside diameter compared to that of 3D model inner diameter varied from 1.52% to 3.9%. Whereas percentage variation of square side of the printed part when compared with 3D model square side varied from 1.01% to 2.83%.

Keywords


Additive Manufacturing, 3D Printing, Fused Deposition Modeling, Surface Roughness, Optimization.

References