Simultaneous multi-objective optimization of stainless steel clad layer on pressure vessels using genetic algorithm

Metal cladding is a process of depositing a filler material to enhance the surface properties of base material using a suitable welding process. In this work the clad specimens are produced by surfacing a layer of filler material using weld cladding process to minimize the heat loss across the walls of the pressure vessels. It is done by depositing a low thermal conductivity austenitic stainless steel grade of 316L on structural steel plates used for boiler construction using flux cored arc welding process. The experimental study is carried out as per design of experiments availed for five factors five levels central composite design using response surface methodology. The mathematical models are developed for the prediction of clad layer height, clad layer width and depth of penetration. These models are employed in formulating fitness functions for multi-objective optimization of clad layer dimensions using genetic algorithm (GA). The set of optimal solutions suggested by response surface optimizer and genetic algorithm are compared and discussed. Conformity tests are conducted to validate the prediction capability of developed models and optimum settings. Optimum clad layer dimensions have been arrived and optimized stainless steel clad specimen has been produced. The heat transfer analysis is planned to be conducted in the next phase. The findings can be used in energy efficient design of pressure vessels.