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Military and unmanned aerial vehicles (UAV) applications like rocket motor casings, missile covers and ship hulls use components that are made of maraging steel. Maraging steel has properties that are superior to other metals, making it more suitable for the fabrication of such components. A grey relational analysis (GRA) that is based on the Taguchi method has been utilised in the current study to optimise a laser beam welding (LBW) process. Further aspects such as GRA's optimum ranges and percentage contributions were also estimated.

A Taguchi L16 orthogonal array is utilised to design and conduct the experiments. Laser power (LP), welding speed (WS) and focal position (FP) are the three parameters are chosen for the process of welding. The output responses are the upper width of the heat-affected zone (HAZup), the upper width of the fusion zone (FZup) and the depth of penetration (DOP). The effect of the above key parameters on the responses was examined using an analysis of variance (ANOVA).

The results of ANOVA reveal that the parameter that has the most influence on the overall grey relational grade (GRG) is the FP. Finally, metallographic characterisation and a microstructural analysis are conducted on the weld bead geometry to demarcate the zone of HAZ and fusion zone (FZ).

As the most important criteria for LBW of maraging steels is the provision of higher DOP, higher FZ width and lower heat-affected zone, the study intended to prove the applicability of GRA technique in solving multi-objective optimisation problems in applications like defence and unmanned systems.

The purpose of this paper is to optimize the fusion zone grain size and hardness using Hooke and Jeeves Algorithm.

Experiments are conducted as per four factors, five levels response surface method based central composite design matrix. Empirical relations for predicting grain size and harness are developed. The effect of welding variables on grain size and hardness are studies. Grain size and hardness are optimised using Hooke and Jeeves Algorithm.

The developed empirical relations can be effectively used to predict grain size and hardness values of micro plasma arc welded Inconel 625 sheets. The values of grain size and hardness obtained by Hooke and Jeeves Algorithm matches with experimental values with great accuracy.

The developed mathematical models are valid for 0.25 mm thick Inconel 625 sheets only.

In the present paper only four important factors namely peak current, back current, pulse rate and pulse width are considered, however one may consider other parameters like plasma gas flow rate, shielding gas flow rate, etc.

The present work is very much useful to sheet metal industries manufacturing metal bellows, diaphragms, etc.