Hole making is an important phase in composite machining as structural applications of composites require assemblage. To do so, abrasive waterjet machining (AWM) is recommended by several fabricators and researchers. The quality of the holes produced in composites severely affects the durability of assembled structures. Hence, exploring this aspect is important. In this context, the current study investigates the influence of the AWM variables on GFRP composites. Here, cutting speed (V_c), and abrasive flow rate (Q_ab) are selected as input variables whereas the output attributes are the material removal rate (MRR), surface roughness (R_a), roundness (R_o), and cylindricity (C_y). Initially, mathematical models (objective functions) are derived using statistics of nonlinear regression for correlating the aforementioned variables and output attributes. In the next phase, the study utilizes recently developed Rao algorithms i.e. Rao 1, Rao 2, and Rao 3 to determine the ideal machining condition as V_c = 100 cm/min, and Q_ab = 300 gm/min. The results were also compared with the JAYA and TLBO approaches in order to show the effectiveness of the proposed methodology and it was observed that exploration of Rao 1, Rao 2, and Rao 3 algorithms appears more fruitful in terms of computational time and effort.

RMD™ welding has been developed for a variety of steels to regulate the rate of metal transfer effectively during the short-circuiting mode of the GMAW process. To achieve the desired weld quality, distinct process variables must be tuned precisely, which leads to an encouraging field of research known as parametric optimization. In this context, the gas flow rate (GFR), current (A), and voltage (V) were chosen as welding variables, and their effects have been examined for the depth of penetration (DOP) and heat-affected zone (HAZ). The work aims to determine favorable parameter settings besides optimizing the aforementioned variables of RMD^TM arc weldments. Hence, the satisfaction function approach has been implemented with the Taguchi method to evaluate the favorable process combination. Furthermore, the aforementioned welding variables were again optimized using NSGA II methodology, and a Pareto-front was also drawn for partially evaluating a set of actions with multi-dimensional outputs. The obtained Pareto optimal (PO) solutions aids in revealing the relationship between the performance characteristics and uncover the functioning of the process in an ideal manner. A confirmatory test was also performed, which validates the obtained optimal settings as 100 A current with 16 V voltage and 21 L/min. gas flow rate.