Magnesium-Calcium (Mg-Ca) alloy has received considerable attention as an emerging biodegradable implant material in orthopedic fixation applications. The biodegradable Mg-Ca alloys avoid stress shielding and secondary surgery inherent with permanent metallic implant materials. They also provide sufficient mechanical strength in load carrying applications as opposed to biopolymers. However, the key issue facing a biodegradable Mg-Ca implant is the fast corrosion in the human body environment. The ability to adjust degradation rate of Mg-Ca alloys is critical for the successful development of biodegradable orthopedic implants. This paper focuses on the functions and requirements of bone implants and critical issues of current implant biomaterials. Microstructures and mechanical properties of Mg-Ca alloys, and the unique properties of novel magnesium-calcium implant materials have been reviewed. Various manufacturing techniques to process Mg-Ca based alloys have been analyzed regarding their impacts on implant performance. Corrosion performance of Mg-Ca alloys processed by different manufacturing techniques was compared. In addition, the societal and economical impacts of developing biodegradable orthopedic implants have been emphasized.

This paper presents a review of the state-of-art research on surface integrity characterization, especially the characteristics of residual stresses produced in machining of hardened steels, titanium and nickel-based superalloys using the geometrically defined tools. The interrelationships among residual stresses, microstructures, and tool-wear have been discussed. Current research on residual stress modeling and simulation using finite element method has been critically assessed. Also, the rationale for developing multi-scale simulation models for predicting residual stresses in machining has been presented. At the end, possible future work has been proposed.

Selective laser melting (SLM) is widely used in making three-dimensional functional parts layer by layer. Temperature magnitude and history during SLM directly determine the molten pool dimensions and surface integrity. However, due to the transient nature and small size of the molten pool, the temperature gradient and the molten pool size are challenging to measure and control. A three-dimensional finite element (FE) simulation model has been developed to simulate multilayer deposition of Ti-6Al-4 V in SLM. A physics-based layer buildup approach coupled with a surface moving heat flux was incorporated into the modeling process. The melting pool shape and dimensions were predicted and experimentally validated. Temperature gradient and thermal history in the multilayer buildup process was also obtained. Furthermore, the influences of process parameters and materials on the melting process were evaluated.

Rapid heating and cooling thermal cycle of metals in selective laser melting (SLM) generates high tensile residual stress which leads to part distortion. However, how to fast and accurately predict residual stress and the resulted part distortion remains a critical issue. It is not practical to simulate every single laser scan to build up a functional part due to the exceedingly high computational cost. Therefore, scaling up the material deposition rate via increasing heat source dimension and layer thickness would dramatically reduce the computational cost. In this study, a multiscale scalable modeling approach has been developed to enable fast prediction of part distortion and residual stress. Case studies on residual stress and distortion of the L-shaped bar and the bridge structure were presented via the deposition scalability and validation with the experimental data. High residual stress gradient in the building direction was found from high tensile on the surface to high compressive in the core. The part distortion can be predicted with reasonable accuracy when the block thickness is scaled up by 50 times the layer thickness from 30 μm to 1500 μm. The influence of laser scanning strategy on residual stress distribution and distortion magnitude of the bridges has shown that orthogonal scanning pattern between two neighboring block layers is beneficial for reducing part distortion.

Work materials experience large strains, high strain rates, high temperatures, and complex loading histories in machining. The problem of how to accurately model dynamic material behavior, including the adiabatic effect is essential to understand a hard machining process. Several conventional constitutive models have often been used to approximate flow stress in machining analysis and simulations. The empirical or semiempirical conventional models lack mechanisms for incorporating isotropic/kinematic hardening, recovery, and loading history effects. In this study, the material constants of AISI 52100 steel (62 HRc) were determined for both the Internal State Variable (ISV) plasticity model and the conventional Johnson-Cook (JC) model. The material constants were obtained by fitting the ISV and JC models using nonlinear least square methods to same baseline test data at different strains, strain rates, and temperatures. Both models are capable of modeling strain hardening and thermal softening phenomena. However, the ISV model can also accommodate the adiabatic and recovery effects, while the JC model is isothermal. Based on the method of design of experiment, FEA simulations and corresponding cutting tests were performed using the cutting tool with a $20$ deg chamfer angle. The predicted chip morphology using the ISV model is consistent with the measured chips, while the JC model is not. The predicted temperatures can be qualitatively verified by the subsurface microstructure. In addition, the ISV model gave larger subsurface von Mises stress, plastic strain, and temperature compared with those by the JC model.