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Carbon Fiber Reinforced Plastic (CFRP) composite laminates are widely used in aerospace and aircraft structural components due to their superior properties. However, they are regarded as difficult-to-cut materials because of bad surface quality and low productivity. Drilling is the most common hole making process for CFRP composite laminates and drilling induced delamination damage usually occurs severely at the exit side of drilling holes, which strongly deteriorate holes quality. In this work, the candle stick drill and multi-facet drill are employed to evaluate the machinability of drilling T700/LT-03A CFRP composite laminates in terms of thrust force, delamination, holes diameter and holes surface roughness. S/N ratio is used to characterize the thrust force while an ellipse-shaped delamination model is established to quantitatively analyze the delamination. The best combination of drilling parameters are determined by full consideration of S/N ratios of thrust force and the delamination. The results indicate that candle stick drill will induce the unexpected ellipse-shaped delamination even at its best drilling parameters of spindle speed of 10,000 rpm and feed rate of 0.004 mm/tooth. However, the multi-facet drill cutting at the relative lower feed rate of 0.004 mm/tooth and lower spindle speed of 6000 rpm can effectively prevent the delamination. Comprehensively, holes quality obtained by multi-facet drill is much more superior to those obtained by candle stick drill.

The major purposes of this research are to improve the process yield rate for air cleaners in Toyota Corona vehicles and to find the robust parameters of this process by using the Taguchi method and design for the experiments. Furthermore, in order to reduce the scrap cost, improve the quality of plastic injection and decrease environmental pollution, we aim to reduce the occurrence of nonconformities and increase the use of recycled material.

Within the analysis of the injection mold, we would like to study the correlation between injecting conditions and nonconformities by using the orthogonal table of L₁₈. Based on the results of the S/N ratio, ANOVA, and response surface methods, we have given suggestions for the optimal conditions for the specifications of the parameters and the standard of the process. Moreover, the results of this research can be applied to other products.

Finally, we expect to develop software which can apply the Taguchi methodology and is user friendly for both suppliers and users of video instruction. Furthermore, the Taguchi method will be generally applied to other component processing methods involving other vehicles.

Wire cut electric discharge machining (WCEDM) is a flexible and more essential for the precise machining of hard materials like composites and super alloys. In order to improve the surface texture as the main focus of the WCEDM process, the expansion of the fundamental procedural perceptive is very important. This paper mainly focuses on the prediction of surface quality of Al-Fe-Si alloy (AA8011) matrix composites during the WCEDM process. For the fabrication of composites, the varying proportions (0, 5, 10 and 15 wt.%) of ZrO₂ ceramic particle were incorporated with AA8011 matrix alloy by using stir casting method. In the machining studies, to investigate the effects of reinforcement (wt. %) and the WCEDM process parameters, namely pulse current (amps), pulse-on time ($\mu$s) and pulse-off time ($\mu$s) on machining performance like surface roughness (SR) of the proposed composites. Based on the selection of parameters and their levels, an L16 (4⁴) orthogonal array was most suitable for conducting the WCEDM experiments. A Taguchi technique was employed in this study to determine the optimal conditions of machining parameters through the signal-to-noise (S/N) ratio analysis. The result shows that the minimum SR is achieved at 5 wt.% of reinforcement, 6 amps of pulse current, 110 $\mu$s of pulse-on time and 50 $\mu$s of pulse-off time, respectively. Analysis of variance (ANOVA) results revealed that the reinforcement wt.% has the primary significant factor on SR, trailed by pulse-on time and pulse current, respectively. Furthermore, the regression equation was also developed to predict the SR and that values well agree with the experimental SR.

As the population of the world is continuously increasing, demand of the mechanical manufactured products is also increasing. Machining is the most important process in any mechanical manufacturing, and in machining two factors, i.e. material removal rate (MRR) and surface roughness (SR) are the most important responses. If the MRR is high, the product will get desired shape in minimum time so the production rate will be high, but we could not scarify with the surface finishing also because in close tolerance limit parts like in automobile industry, if the surface is rough exact fit cannot take place.

The term optimization is intensively related to the field of quality engineering. Abrasive water jet machining is an important unconventional machining, in order to obtain better response, i.e. material removal rate and surface roughness. Various process parameters of AWJM need to be observed and selected to improve machining characteristics. Better machining characteristics can be achieved by optimizing various process parameters of AWJM.

This study considers four process control parameters such as transverse speed, standoff distance, abrasive flow rate and water pressure. The response is taken to be material removal rate and surface roughness. The work piece for stainless steel AISI 304 material of size 15 cm × 10 cm × 2 cm is selected for experiments. Sixteen experimental runs (two trials for each experimental runs) were carried out for calculating MRR and SR and average value of these two trials have been taken for analysis. MRR is normalized according to higher-is-better and SR is normalized according to lower is better. The experiment data analysis is done and VIKOR index is found. Finally, the analysis of VIKOR index using S/N ratio is done and found the most significant factor for AWJM and predicted optimal parameters setting for higher material removal rate and lower surface roughness. Verification of the improvement in quality characteristics has been made through confirmation test with the predicted optimal parameters setting. It is found that the determined optimum combination of AWJM parameters gives the lowest VIKOR INDEX which shows the successful implementation of VIKOR Method coupled with S/N ratio in AWJM.