This paper deals with development of structural equation models for two wire electrical discharge machining (WEDM) processes so as to investigate and estimate their machining performance along with identification of the most significant input parameters influencing the operational achievement of the said processes. These models also search out the corresponding responses to be treated as the best performance indicators for both the WEDM processes. Based on the experimental and simulated datasets, two models are subsequently developed showing the relationships between the input parameters, responses and machining performance for each of the considered WEDM processes. For both the processes, it is observed that the second model, developed without considering the insignificant input parameters, has better goodness-of-fit value as compared to the first model where all the WEDM process parameters are contemplated as the predictor variables. It can be revealed that pulse-on time is the most important predictor of machining performance with standardized coefficients of 0.61 and 0.75 respectively for the two WEDM processes. Machining rate acts as the main indicator variable in the first experimental dataset, while gap current is the most significant indicator variable in the second experimental dataset with factor loadings of 0.98 and 0.92 respectively

Diamond-like carbon (DLC) is becoming increasingly popular due to its several superior mechanical, chemical, tribological and optical properties. However, achievement of these advantageous properties of DLC coatings mainly depends on various input parameters involved in its deposition process. Recently,the DLC researchers have started tapping the potential of different optimization techniques for its better design, functionality and applicability. In this paper, three optimization tools, i.e. weighted-sum multi-objective optimization, Pareto multi-criteria decision making (MCDM) technique and optimal prediction based on level averaging post-MCDM are applied for determination of the optimal parametric combination of a thermal chemical vapor deposition (CVD) process for better DLC application. It is observed that the choice of the optimization technique has a significant role on the optimal DLC performance. The observations are reported based on 20 experiments of DLC deposition on silicon substrates using thermal CVD process. The optimal settings of deposition temperature, and hydrogen and acetylene flow rates are identified based on simultaneous optimization of two tribological properties, i.e. coefficient of friction and wear rate of the DLC coatings. It is propounded that the Pareto MCDM technique can provide the most balanced solution.