Experimental Study on Dimensional Accuracy of FDM Build Part

Abstract

Rapid prototyping is a broad term used for all number of technologies which enable fabrication of part directly from CAD data source. As compare to traditional method like forging and milling which are based on formative and subtractive principles respectively, these techniques are based on additive principle. Fused deposition modeling is a type of rapid prototyping process used for manufacturing a part in minimum possible time, without using tool and human intervention. Rapid prototyping is having advantage like continuous and rapid changes in manufacturing in shortest manufacturing time due to which it is more attracted towards manufacturing industries. Among all available Rapid prototyping processes, fused deposition modeling (FDM) uses thermoplastic filament in semi molten state which extruded from tip of nozzle for building a part in layer by layer deposition method. FDM processes has its own limitation related with accuracy, strength and surface finish etc. Hence, it is necessary to understand the factors which are affecting the quality of FDM part. This study focuses on the improvement of dimensional accuracy of FDM build part by controlling the processes parameters. The process parameter viz. layer thickness, orientation, raster angle and number of contours along with their interaction affects the dimensional accuracy of FDM processed ABSM30 ( Acrylonitrile-butadine-styrene ) part. For improving the dimensional accuracy, response surface methodology is adopted; it is found that different factors and their interaction control the part dimensions along different direction. Due to shrinkage of semi molten thermoplastic material extruded from nozzle is the major cause of dimensional inaccuracy. Dimensional inaccuracy can be expressed as diametric deviation, volumetric deviation, deviation of angle and circularity. For obtaining optimal parameter setting for improving overall dimension of the part, grey relation analysis with response surface methodology is used.