Additive manufacturing (AM) has been gaining ground as a quick, robust, and highly versatile alternative over conventional manufacturing processes to fabricate various customized products with complex designs for a broad spectrum of materials. AM is a process of fabricating a three-dimensional (3D) object by adding material in a layer-by-layer fashion. One of the widespread methods of AM for processing polymers is fused filament fabrication (FFF) [1]. The scientific and industrial communities working on polymers have shifted their focus to bio-based materials that can replace petroleum-based plastics in applications where sustainability and environmental awareness are paramount [2]. Among various available biopolymers for FFF, aliphatic polyesters like polyhydroxyalkanoates (PHAs) are very useful due to their bio-origin (directly from bacteria), biocompatibility, and enhanced biodegradability. PHAs are known for their complete biodegradability without leaving any microplastics when discharged into extreme environments like soil or water [3]. 3D printing of PHA is quite difficult and has printing limitations due to high viscosity when melted, making it challenging to achieve consistent flow and uniform layer thickness causing dimensional inaccuracy [4]. PHA also has a low melt strength, due to which it may collapse or deform before solidifying. Moreover, fast crystallization and physical aging of PHA at room temperature lead to shrinkage that causes bed adhesion problems. Therefore, to solve the challenges mentioned above of 3D printing PHA, the present research focuses on detailed printability studies like warpage calculation and evaluation of dimensional accuracy for various process parameters. The surface roughness of the 3D printed part plays a major role in multiple applications like biomedical devices, consumer goods, and aesthetics. A detailed study on the effect of varying process parameters on surface roughness values has been conducted using a non-contact optical profilometer. The process parameters considered for the present study are layer thickness, extruder temperature, bed temperature, printing speed, and infill density, along with a DoE-based approach for regression analysis based on further optimization.

References

[1] I. Gibson, D. W. Rosen, and B. Stucker, “Development of Additive Manufacturing Technology,” in Additive Manufacturing Technologies: Rapid Prototyping to Direct Digital Manufacturing, Boston, MA: Springer US, 2010, pp. 36–58. doi: 10.1007/978-1-4419-1120-9_2.

[2] E. A. MacGregor, “Biopolymers,” in Encyclopedia of Physical Science and Technology (Third Edition), Third Edit., R. A. Meyers, Ed. New York: Academic Press, 2003, pp. 207–245. doi: https://doi.org/10.1016/B0-12-227410-5/00064-8.

[3] S. A. Acharjee, P. Bharali, B. Gogoi, V. Sorhie, B. Walling, and Alemtoshi, “PHA-Based Bioplastic: a Potential Alternative to Address Microplastic Pollution,” Water, Air, Soil Pollut., vol. 234, no. 1, p. 21, 2022, doi: 10.1007/s11270-022-06029-2.

[4] M. Mehrpouya, H. Vahabi, M. Barletta, P. Laheurte, and V. Langlois, “Additive manufacturing of polyhydroxyalkanoates (PHAs) biopolymers: Materials, printing techniques, and applications,” Mater. Sci. Eng. C, vol. 127, p. 112216, 2021, doi: https://doi.org/10.1016/j.msec.2021.112216.