Purpose Due to intrinsic limitations, fused deposition modelling (FDM) products suffer from the bad surface finish and inaccurate dimensional accuracies restricting its usage in many applications. Hence, there is a need for processing polymer patterns before, during and after their productions. This paper aims to highlight the importance of pre- and post-processing treatments on the FDM-based acrylonitrile butadiene styrene patterns improving its surface quality so, that it can be used in rapid investment casting process for making medical implants and other high precision components. Design/methodology/approach As a part of pre-processing treatment, the machine parameters affecting the surface quality were identified and optimised using design of experiments. The patterns developed after the first stage of optimisation were given different post-processing treatments, which included vapour smoothening, chemical treatment and sand paper polishing. The results were compared and the best ones were used for making patterns for making medical implants via rapid investment casting technique. The surface quality was checked while the dimensional changes happening during the stages of this hybrid technique were recorded using a three-dimensional optical scanner. Findings The surface roughness of the FDM based ABS patterns reduced from 21.63 to 14.40 µm with pre-processing treatments. Chemical treatment (post-processing treatment) turned to be the most suitable technique for reducing the surface roughness further down to 0.30 µm. Medical implants that used these pre- and post-processing treatments gave an average surface roughness of 0.68 µm. Cost and lead time comparisons showed that rapid investment casting technique can be a better method for low volume, customised and with specific requirements. Originality/value FDM parts/medical implants produced by rapid investment casting technique suffer from the inferior surface finish and inaccurate dimensional accuracies limiting its applications. A systematic approach to overcome this issue is presented in this research paper. This will directly help the end users and the manufacturers of medical implants, wherein, better surface finish and dimensionally accurate components are expected.

No abstract

The present research work is focussed on establishing the complex nonlinear input-output relations of a furan resinbased molding sand system. Further, a set of input parameters, which will result in optimized mold properties, is determined. Grain fineness number, setting time, percentage of resin, and hardener are considered as process variables. Mold properties, such as green compression strength, shear strength, mold hardness, gas evolution, permeability, and collapsibility are treated as the process outputs. Nonlinear input-output relations have been developed and statistical analysis has been carried out by utilizing design of experiments, central composite design. Surface plots are developed to study and analyze the input-output relations. The input parameters that will result in best molding conditions and improve casting quality characteristics are determined by utilizing desirability function approach and multiple particle swarm optimization-based crowding distance (MOPSO-CD) techniques. The optimum value for the process variables namely grain fineness number, furan resin, hardener, and setting time are found to be equal to 55, 1.85, 1.2, and 60, respectively. The quality characteristics of the castings namely yield strength, ultimate tensile strength, hardness, density, and secondary dendrite arm spacing are found to improve by 14.03%, 15.08%, 14.14%, 12%, 2.22%, and 12.24%, respectively for the castings made in optimized molding sand conditions.

3D printing technology is making its mark in automotive, aerospace, and bio-medical-related industries. It is considered a viable option for the direct manufacturing of final parts. However, it is not possible to print longer parts in a single attempt due to the bed size limitation of printers. This problem can be addressed by employing a polymer joining technique as a secondary operation. Moreover, low mechanical strength and inferior geometrical qualities like the flatness of the joined parts restrict its real-time industrial application. Here, an attempt is made to join a longer part (typical of an aircraft wing) using friction stir welding technique. Joining was performed on 3D printed similar/dissimilar thermoplastic parts. Tensile test results showed that friction stir welding of 3D printed parts (for both similar/dissimilar) produced relatively weaker joints compared to the base material. Various important process parameters of 3D printing and friction stir welding technique, namely part infill percentage, material combination, tool rotational speed, traverse speed, and tool pin taper angle were optimized by means of ANOVA. Optimization was aimed at maximizing the weld strength, elongation, hardness, and desired flatness. The results suggested that the material combination and tool pin taper angle play a significant role in the weld's strength as well as its geometric properties (flatness). The results were validated by adopting the optimized parameters for successful joining of the wing section of an unmanned aerial vehicle. A span of 320 mm, with a metrological acceptable flatness value of 0.41 µ/m could be successfully achieved on an existing 3D printer whose bed size limit was 240 mm.

No abstract