The selected laser melting production and subsequent post-processing of Ti-6Al-4V prosthetic acetabular

&nbsp;Processing and post processing of human prosthetic acetabular cup by using 3D printing. The results showed using 3D printers leads to fabrication customized implants with higher quality.<br /

Thermal Stress Flow Analysis in Fabrication of Acetabular Shells Using SLM

Additive Manufacturing (AM), more popularly known as 3D Printing, is a process for producing functional artifacts by adding layers of materials from data generated directly from 3D solid CAD models. Additive Manufacturing (AM) is the formalized term for what used to be called Rapid Prototyping and what is commonly referred to as 3D Printing. The key to how AM works is that parts are made by adding layers of material; each layer corresponding to a thin cross-section of the part derived from the original CAD data. Although most AM machines produce parts using polymers, there are an increasing number of machines that can directly fabricate in metals. The majority of these machines fabricate from raw material in powder form using a directed energy beam to create a local melt zone. Total hip replacement is recommended for people who have medical issues related to excessive wear of the acetabular, osteoarthritis, accident or age. Researches have shown that large numbers of hip arthroplasties (where the articular surface of a musculoskeletal joint is replaced), hip remodelling, or realignment are carried out annually and will increase in the next few decades. Manufacturing of acetabular shells by using AM is a promising and emerging method that has a great potential to improve public health. Lost wax casting or investment casting is currently used to produce acetabular shells followed by lengthy and complex secondary processes such as machining and polishing. Living organs and medical models have intricate 3D shapes that are challenging to identity in X-ray CT images. These images are used for preparing treatment plans to improve the quality of the surgeries regarding waiting and surgery time per procedure and care regime. For instance, a limited number of hip replacement procedures can be carried out on each acetabulum due to a decrease of bone thickness. Rapid prototyping is a suitable treatment planning tool in complex cases to enhance the quality of surgical procedure and provide long-term stability that can be used to customize the shape and size of the acetabular shell. In this paper, to analyse the manufacturing of a prosthetic acetabular shell, built-up lines resulting from a thermal stress flow and process stopping during the selective laser melting (SLM) AM process, with regarding Gibbs free energy, interfacial energy, and equilibrium temperature will be discussed. Geometrical measurements showed 1.59% and 0.27% differences between the designed and manufactured prototype for inside and outside diameter respectively. Experimental results showed that thermal stress flow in outer surfaces are compressive, but for inner surfaces are tensile, so built-up lines in inner and outer surfaces appear as a groove and dent respectively. The results also indicate that SLM is an accurate and promising method for fabrication of acetabular cup

An accurate PSO-GA based neural network to model growth of carbon nanotubes

By combining particle swarm optimization (PSO) and genetic algorithms (GA) this paper offers an innovative algorithm to train artificial neural networks (ANNs) for the purpose of calculating the experimental growth parameters of CNTs. The paper explores experimentally obtaining data to train ANNs, as a method to reduce simulation time while ensuring the precision of formal physics models. The results are compared with conventional particle swarm optimization based neural network (CPSONN) and Levenberg&ndash;Marquardt (LM) techniques. The results show that PSOGANN can be successfully utilized for modeling the experimental parameters that are critical for the growth of CNTs

The effect of vibration during friction stir welding on corrosion behavior, mechanical properties, and machining characteristics of stir zone

Different methods have been applied to refine various characteristics of the zone (or nugget) obtained by friction stir welding (FSW). In the current research, joining components are vibrated normal to the weld line during FSW to refine the zone microstructure. This process is described as friction stir vibration welding (FSVW). The effect of FSVW on mechanical properties, corrosion behavior, and machining characteristics of the zone are investigated. Al5052 alloy specimens are welded using FSW and FSVW processes and their different characteristics are compared and discussed. The results show that the strength and ductility of the welded parts increase when the vibration is applied. The outcomes also show that corrosion resistance of the nugget for FSV-welded specimens is lower than FS welded samples, and machining force of the former specimens is higher than the latter ones. These are related to smaller grain size in the zone of FSV-welded specimens compared to FS welded parts. Smaller grain size leads to a greater volume fraction of grain boundaries and, correspondingly, higher strength and hardness, as well as lower corrosion resistance

Numerical and analytical investigation on meltpool temperature of laser-based powder bed fusion of IN718

Prediction of meltpool features in Laser-Based Powder Bed Fusion (LB-PBF) is a complex non-linear multiple phase dynamic problem. In this investigation, numerical simulations and analytical models are offered to predict meltpool temperature and to provide a methodology to estimate melt track quality. By determining the meltpool temperature, different rheological phenomena including recoil pressure can be controlled. Recoil pressure is known to drive the keyhole and conduction modes in LB-PBF which is an important factor to qualify the melt track. A numerical simulation was carried out using Discrete Element Method (DEM) with a range of process parameters and absorptivity ratios; allowing observation of the variation of meltpool temperature and free surface morphology, as calculated by the volume-of-fluid (VOF) method. A spatially thermophysical-based analytical model is developed to estimate meltpool temperature, based on LB-PBF process parameters and thermophysical properties of the material. These results are compared with experimentally observed meltpool depth for IN718 specimens and found to have a good accuracy. The numerical and analytic results show good agreement in the conduction mode to estimate the meltpool temperature and related phenomena such as recoil pressure to control the melt track and layering quality. The analytical model does not accurately predict the keyhole mode which may be explained by evaporation of chemical elements in the examined material

An Overview: Laser-Based Additive Manufacturing for High Temperature Tribology

Laser-based additive manufacturing (LBAM) is a versatile manufacturing technique, extensively adopted to fabricate metallic components of enhanced properties. The current review paper provides a critical assessment of the fabricated metallic coatings and parts through LBAM-processes [e.g., laser metal deposition (LMD) and selective laser melting (SLM)] for high temperature tribological applications. A succinct comparison of LBAM-fabrication and conventional manufacturing is given. The review provides an insight into the sophisticated application-driven material design for high temperature tribological contacts. The review highlights the major mechanisms behind the improvement in the tribology of the laser-deposits; properties evolving as a consequence of the microstructure, lamellar solid lubricants, sulfides, soft metals, lubricious oxides, and self-lubricating surfaces

A comprehensive study on meltpool depth in laser-based powder bed fusion of Inconel 718

One problematic task in the laser-based powder bed fusion (LB-PBF) process is the estimation of meltpool depth, which is a function of the process parameters and thermophysical properties of the materials. In this research, the effective factors that drive the meltpool depth such as optical penetration depth, angle of incidence, the ratio of laser power to scan speed, surface properties and plasma formation are discussed. The model is useful to estimate the meltpool depth for various manufacturing conditions. A proposed methodology is based on the simulation of a set of process parameters to obtain the variation of meltpool depth and temperature, followed by validation with reference to experimental test data. Numerical simulation of the LB-PBF process was performed using the computational scientific tool “Flow3D Version 11.2” to obtain the meltpool features. The simulation data was then developed into a predictive analytical model for meltpool depth and temperature based on the thermophysical powder properties and associated parameters. The novelty and contribution of this research are characterising the fundamental governing factors on meltpool depth and developing an analytical model based on process parameters and powder properties. The predictor model helps to accurately estimate the meltpool depth which is important and has to be sufficient to effectively fuse the powder to the build plate or the previously solidified layers ensuring proper bonding quality. Results showed that the developed analytical model has a high accuracy to predict the meltpool depth. The model is useful to rapidly estimate the optimal process window before setting up the manufacturing tasks and can therefore save on lead-time and cost. This methodology is generally applied to Inconel 718 processing and is generalisable for any powder of interest. The discussions identified how the effective physical factors govern the induced heat versus meltpool depth which can affect the bonding and the quality of LB-PBF components

Metallic Additive Manufacturing: Design, Process, and Post-Processing

The first modern additive manufacturing machines, developed in the early 1990s, primarily made parts using polymers [...