A grey-based Taguchi method was applied to investigate the optimal operating conditions in shielded metal arc welding (SMAW) to join SS316 and ASTM A36. This work aims to set optimal parameters for the mechanical properties of the weld joint. The effects of various welding factors on electrode type, welding current, arc welding, and welding speed have to be characterized and optimized to achieve an optimum condition. An L9 orthogonal array was used to group the various components. The mechanical properties of a dissimilar weld joints were described through hardness, tensile and flexural strength tests. The optimum welding parameters were obtained simultaneously as an electrode type E309, a welding current of 100 A, an arc voltage of 14 V, and a welding speed of 4 cm/min, which predicted improve 23.0% in its performance.

The combination of metallic bio-inert material, stainless-steel 316L (SS316L) and a bio-active material, hydroxyapatite (HA) can produce a composite which has superior properties for orthopaedic applications. The main objective of this study is to investigate the effects of sintering temperature and holding time on the physical and mechanical properties of the sintered part. 50wt.% SS316L and 50wt.% HA were mixed with a binder system of palm stearin (PS) and polyethylene (PE) at 61 vol.% powder loading. Rheological properties show a pseudo-plastic behaviour of the feedstock, where viscosity decreases with increasing shear rate. The feedstock was injection moulded into a tensile bar shape while thermal debinding was carried out at 320°C and 500°C. The brown parts were sintered at 1000, 1100, 1200 and 1300°C, with three different sintering times of 1, 3 and 5 hours in the furnace. It was found that the highest sintered density measured was 95.61% of the theoretical density. In addition, the highest hardness and Young’s modulus measured were 150.45 HV and 52.61 GPa respectively, which are higher than those of human bone. The lowest percentage of carbon content was 0.022wt.% given by the sample sintered at 1300°C for 1 hour. Therefore, SS316L/HA composite with good mechanical and physical properties was successfully produced through the PIM process.

Recently research on hydroxyapatite bioceramic material has been carried out rapidly to support the needs in the medical field. The study aims to develop porous bioceramic from hydroxyapatite Al₂O₃ composites. Porous hydroxyapatite Al₂O₃ composites were prepared with variation of the weight fraction of Al₂O₃ reinforcement and green bean starch space holder used as porous maker. The manufacturing process begins by mixing hydroxyapatite powder (200 μm), Al₂O₃ powder (55 μm) and green bean powder (200 μm) using a Ballmill with a rotating speed of 225 rpm for 1 hour. The mixture is then put into a mold and compressed in a unidirectional compression device at a pressure of 2000 psi. Green body specimens are then sintered at a temperature of 1200°C and holding time for 3 hours. The apparent density test was carried out using the Archimedes’ method and the highest density was 1.95 g / cm3 with 41.915% porosity in the specimen with 25% Al₂O₃ weight fraction. The results of the compressive test showed that specimens with a weight fraction of 25% Al₂O₃ had the highest compressive strength of 1.01 MPa with a porosity of 41.915%. The morphology observation using the Scanning Electron Microscopy (SEM) showed interconnecting porous had been formed.

The paper presents a potential study on prediction of surface roughness in side milling by optimization techniques approaches. Two methods, response surface methodology (RSM) and artificial neural networks (ANN) were used for optimized prediction. The model of surface roughness was expressed as the main parameter in side milling term of cutting speed, feed rate and axial depth of cut. Rotatable central composite design (RCCD) is employed in developing second-order response surface mathematical model. The ANN model using a multi-layer feed forward, back propagation and training function Levenberg-Marquardt (LM) algorithm with a single hidden layer. Vegetable oils have often been recommended as sustainable alternative cutting fluid since the ecological and health impacts in the use of mineral oil have been questioned and also the rising cost of mineral oil. The advantages of oxidative stability of coconut oil as vegetable oil were utilized in this study to investigate surface roughness of low carbon steel. The machining of ferrous alloy like steel is sometimes a difficult task. This study used uncoated tool because it is suitable when turning and milling alloy. Flood condition was selected because it has been proved effective at low cutting speed. The analysis predicted by RSM and ANN models resulted a good agreement between the experimental and predicted values. The results indicated that the ANN model predict with more accurate compared with the RSM model.