Abstract
The ship hull’s hydro-blasting is a significant part of maintenance in the maritime industry. It absorbs considerable workforce, money, and time which can be reduced through the use of robotic technologies. A hydro-blasting robot should be performing this task uniformly with minimum time and energy. The conventional optimization techniques may not fit the hydro-blasting robots as the robot’s blasting angle influences uniformity, whereas the nozzle’s sweeping speed affects time and energy. Therefore, in this paper, a novel multi-objective optimization framework is proposed to ensure uniformity in hydro-blasting along with the consumption of minimum time and energy. The NSGA II algorithm is used to compute the optimal blasting angle, which is utilized further to obtain the robot’s optimal sweep angle. Multiple numerical simulations are performed, and the results are validated on a hydro-blasting robot Hornbill, to justify the proposed approach’s effectiveness.
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•The uniformity in hydro-blasting is quantified through the height of the material, that can be blasted off the surface.•The performance measures for uniformity, energy consumption and blasting time are explicitly derived as the cost functions.•These cost functions are optimized for better blasting performance, using a multi-objective genetic algorithm (GA) technique.•The experimental validations confirm the analytical claims presented in the paper.