Selection of optimal processing condition during abrasive wear of in-situ ZA-37/TiCp composites using MCDM technique

The present study attestation has been made towards microstructural characterization, and thereafter investigation on the optimum abrasive wear processing condition of newly developed insitu TiC reinforced ZA37 alloys. The MMC's have been processed by advanced vortex creating in-situ technique. Effects of significant influencing variables like abrasive grain size, percentage of reinforcement, applied load, and sliding velocity on abrasive wear characteristics via wear rates, coefficient of friction and interface temperature was investigated thoroughly. A newly developed, GRA based hybrid RSM approach has been implemented to investigate the optimum processing condition within the specified wear domain. The non-linear characteristics of response variables were demonstrated by developing a quadratic regression model which was the functions of independent process variables. ANOVA has been implemented to identify the percentage contribution of each process variables towards responses. The observation revealed that the abrasive grain size, percentage of reinforcement and applied load contributed significantly to the developed model and thereby on the wear characteristics. Improvements were noticed on the response characteristics attained by implementing both the GRSM and desirability approaches. Significant deviations were obtained on responses (15% on wear rates, 20% on COF and 4% on temperature) implementing two phases of optimal parametric combinations predicted by GRA based hybrid approach. Optical surface profile and corresponding micrograph represent the improved surface quality (Ra, 0.83 mu m vs. Ra, 1.18 mu m) and textures employing the GRSM based hybrid approach indicated settings of the process parameter.

Automated summary

The study focused on microstructural characterization and investigation on the optimum abrasive wear processing condition of newly developed in-situ TiC reinforced ZA37 alloys. Advanced vortex creating in-situ technique was used to process the MMCs. Non-linear characteristics of response variables were demonstrated by developing a quadratic regression model, and ANOVA was implemented to identify the contribution of process variables towards responses. Significant improvements were observed on wear rates, COF, and temperature when implementing optimal parametric combinations predicted by the GRA based hybrid approach.