High Speed Machining for Enhancing the AZ91 Magnesium Alloy Surface Characteristics Influence and Optimisation of Machining Parameters

In this study, optimum machining parameters are evaluated for enhancing the surface roughness and hardness of AZ91 alloy using Taguchi design of experiments with Grey Relational Analysis. Dry face milling is performed using cutting conditions determined using Taguchi L9 design and Grey Relational Analysis has been used for the optimization of multiple objectives. Taguchi’s signal-to-noise ratio analysis is also performed individually for both characteristics and grey relational grade to identify the most influential machining parameter affecting them. Further, Analysis of Variance is carried to see the contribution of factors on both surface roughness and hardness. Finally, the predicted trends obtained from the signal-to-noise ratio are validated using confirmation experiments. The study showed the effectiveness of Taguchi design combined with Grey Relational Analysis for the multi-objective problems such as surface characteristics studies.

Investigating the Effect of Tic Coating Layer on the Surface Roughness of Tungsten Carbide Cutting Tools Using Taguchi Design

In this study, external longitudinal turning operation was performed on (AISI 1020) steel to examine the influences of coating of the cutting tool on the machined surface roughness. The cutting tools used were coated and uncoated cemented carbide inserts. The tests are performed at four spindle speeds (80, 315, 500, and 800) rpm, at each of which two feed rates (0.2 and 0.5mm/rev) and two depth of cut (0.5 and 0.7mm) were used. Taguchi design of experiments (DOE) with a designed mathematical predictive model was used to investigate the effect of the coating layer and determine the machining conditions for minimum surface roughness. Accordingly, a suitable mixed orthogonal array L16 (3*4) was selected. The results showed that the surface roughness produced by using TiC coated inserts for identical machining conditions was lower than that produced due to uncoated tool by 41% to 53%. Regression analysis showed that the non-linear quadratic polynomial equation appears to be more suitable for representing the relation of spindle speed, feed rate, and depth of cut with the surface roughness. Taguchi method and the designed mathematical model had been used to predict the optimal cutting conditions. A confirmation test for the obtained results verified that the designed Taguchi experiments and the designed model successfully investigated the effect of the coating on the surface roughness. Data fit ver.9 and Mtb14 software had been employed to achieve the object of the presented work.

Taguchi Grey Relational Optimization of the Multi-mechanical Characteristics of Kaolin Reinforced Hydroxyapatite: Effect of Fabrication Parameters

Comparative study of kaolin reinforced hydroxyapatite (KHAp) and pure HAp using different production parameters has been done through traditional experimentation. However, the quantitative effect, optimization of kaolin reinforcement and fabrication parameters have not been investigated. Hence, this study examines the effect of kaolin reinforcement, compaction pressure and sintering temperature on the experimental mechanical properties of HAp. Taguchi design assisted by grey relational analysis was employed with L36 (2**2 3**1) orthogonal array. The Minitab 16 software was used to analyze the Taguchi design. The result showed a disparity in kaolin reinforcement as the optimum condition for individual mechanical properties, but the grey relational analysis showed better mechanical properties with kaolin reinforcement, 500 Pa compaction pressure and 1100 oC sintering temperature. The obtained result further revealed kaolin reinforcement as a strong and promising reinforcing material for high strength clinical application, having a contribution of 93.16% on compressive strength of HAp. Therefore, future studies can be conducted in the use of different wt% of kaolin on the multi-response mechanical characteristics of HAp.