Papers by Author: Mohd Hamdi

Abstract: Electrical discharge machining (EDM) is a non-conventional machining technique that is well-known for use in fabricating dies and molds owing to machinability of high hardness materials. Although the electro-thermal mechanism of EDM offers many advantages over other available machining methods, its sluggish nature limits the wide application of such machines for mass production. In this research, adding graphite powder to dielectric is proposed to improve EDM performance factors. Material removal rate (MRR) and average surface roughness (Ra) have been monitored and evaluated after addition of graphite powder to dielectric in electrical discharge milling and sinking. It is found that the presence of powder particles in dielectric fluid enhances the MRR steadily up to ~11 and ~17% for milling and sinking process, respectively. Moreover, the highest enhancement if Ra is ~31% at 1g/l graphite powder concentration for electrical discharge milling and up to ~11% for sinking process. Field emission scanning electron microscopy (FESEM) is used to inspect the machined surfaces. The surfaces machined with graphite powder mixed appear significantly unlike the surfaces machined in pure dielectric. Adding powder to dielectric is found to increase the machined surface hardness by ~26%, from 240 to 302 HV.

Abstract: One of the main issues facing dental implantation, which makes osseointegration and bone remodeling problematical, is a mismatch of mechanical properties between engineered and native biomaterials. Functionally Graded Materials (FGMs) has been proposed as a potential alternative to some conventional implant materials such as titanium for selection in prosthetic dentistry. The idea of FGM dental implant is that the property would vary in a certain pattern to match the biomechanical characteristics required at different regions in the hosting bone. This research presents some important findings for the FGM dental implant design in optimization of material gradient. Due to the nature of the problem, multi-objective optimization methods should apply for solving multi-criteria problems. The Pareto front was determined using the Multi-Objective Particle Swarm Optimization (MOPSO). The obtained results from the MOPSO confirm the results obtained by the Response Surface Methodology (RSM) in addition to offering further improvements.