An optimal design for an engineering optimization problem involves various decision variables and constraints. In engineering applications, objectives under consideration conflict with each other, and optimizing a meticulous solution with respect to a single objective can result in objectionable results with respect to the other objectives. A practical solution to a multi-objective problem is to examine a set of solutions, each of which satisfies the objectives at a satisfactory level without being conquered by any other solution. In this paper, a new population based evolutionary algorithm used to optimize the gear drive with combined objective function which maximises the power, efficiency and minimises the overall weight, centre distance has been considered. The performance of the proposed algorithms is validated and results are compared.

Abrasive Water jet (AWJ) Machining is a recent non-traditional machining process. Major part of this technology is a very high-pressure beam of water and abrasives, which is used for machining. Abrasive water jet drilling of material involves the effect of a high velocity jet of water with entrained abrasive particles on to material to be drilled. This technology is widely used in industry for drilling, difficult to machine materials, milling slots, polishing hard materials, cleaning contaminated surfaces, etc. In the proposed work , the process parameters on surface roughness (Ra) which is an important drilling performance is measured in abrasive water jet drilling of AL6061 . Experiments will be conducted in varying, nozzle traverse speed, abrasive mass flow rate and standoff distance for drilling AL6061 alloy using abrasive water jet drilling process. The effects of these parameters on surface roughness will be studied based on the experimental results and useful recommendations will be given in order to select the suitable process parameters in abrasive water jet drilling of AL6061 alloy.