Evolutionary path generation for reduction of thermal variations in thermal spray coating

Abstract

Thermal spraying is a production process which consists of spraying hot material onto a workpiece surface in order to form a coating of a desired thickness. This paper describes a path generation algorithm for industrial robot-based thermal spraying which generates the desired coating as well as keeps the thermal variation on the object surface during the process low. The problem is formulated as a discrete optimization problem which includes the quality of the particle coating and the physics of heat induction, heat diffusion and cooling of the surface. The optimization problem is solved by an Evolutionary Algorithm. By specific mutation operators, self-adaptation, and dropping the concept of generations, an improvement of the quality of the results of over 25% compared to standard operations is achieved. The evolutionary results overall outperform the solutions generated by the often-used strategy of direction-parallel paths.