Automotive Science and Engineering

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Turning of hardened steels using a single point cutting tool has replaced the cylindrical grinding now as it offers attractive benefits in terms of lower equipment costs, shorter set up time, fewer process setups, higher material removal rate, better surface quality and elimination of cutting fluids compared to cylindrical grinding. In order to obtain desired surface quality by machining, proper machining parameters selection is essential. This can be achieved by improving quality and productivity in metal cutting industries. The present study is to investigate the effect of machining parameters such as cutting speed, feed and depth of cut on surface roughness during dry turning of hardened AISI 4340 steel with CVD (TiN+TiCN+Al2O3+ZrCN) multilayer coated carbide inserts. A full factorial design of experiment is selected for experimental planning and the analysis of variance (ANOVA) has been employed to analyze the significant machining parameters on surface roughness during turning. The results showed that feed (60.85%) is the most influencing parameter followed by cutting speed (24.6%) at 95% confidence level. And the two-level interactions of feed-cutting speed (F*V), depth of cut-feed (D*F) and depth of cutcutting speed (D*V) are found the significant effects on surface roughness in this turning process. Moreover, the relationship between the machining parameters and performance measure i.e. surface roughness has been modeled using multiple regression analysis.

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The current experimental study is to investigate the effects of process parameters (cutting speed, feed rate and depth of cut) on performance characteristics (surface roughness, machining force and flank wear) in hard turning of AISI 4340 steel with multilayer CVD (TiN/TiCN/Al2O3) coated carbide insert. Combined effects of cutting parameter (v, f, d) on performance outputs (Ra, Fm and VB) are explored employing the analysis of variance (ANOVA). An L9 Taguchi standard design of experiments procedure was used to develop the regression models for machining responses, within the range of parameters selected. Results show that, feed rate has statistical significance on surface roughness and the machining force is influenced principally by the feed rate and depth of cut whereas , cutting speed is the most significant factor for flank wear followed by cutting speed. The desirability function approach has been used for multi-response optimization. Based on the surface roughness, machining force and flank wear, optimized machining conditions were observed in the region 147 m/min cutting speed and 0.10 mm/rev feed rate and 0.6 mm depth of cut.

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In this study, the driver airbag geometry and internal pressure were considered as the main parameters to investigate the head injury severity in a frontal crash. The total energy absorption of an airbag was investigated in a drop test simulation and its rate was discussed by the depression distance parameter. On the other hand, the maximum deceleration of the impactor was determined to represent the airbag stiffness by a defined deceleration peak parameter. Thus, the depression distance and the deceleration peak were the objective functions for an isolated airbag under a lumped-mass impact simulation. Furthermore, an optimal matrix was generated using the design method of experiments (DOE) and yielded the airbag parameters as outputs. After the evaluation of the design parameters by the Taguchi method, the ANOVA method was used to predict the most effective parameters. Finally, a sled test with the 50% HYBRID III dummy and the defined airbag was simulated. An experimental crash was selected as the reference point to verify the simulation and to be used to compare the outcomes. Even though the objective function of depression distance showed contradictory effects to reduce the head injury severity, the results showed a %16.4 reduction in the driver head injury in a full-frontal crash.