Robot path optimization for laser cladding forming

Abstract

Purpose

The purpose of this paper is to provide an optimization method of robot cladding path, which is helpful to solve the problem of path under-optimization in laser cladding forming (LCF) based on robot.

Design/methodology/approach

First, the error influence parameters need setting before the cladding path generation, and the model of seeking appropriate error influence parameters is established based on the particle swarm optimization (PSO). Second, to solve the problem of collapse during the LCF process, the reason for collapse is analyzed and a robot cladding path error optimization method based on the layer path interpolation is proposed. Finally, the simulation and experiments are carried out.

Findings

Under the premise of giving the expected error of stereo lithography (STL) model, the optimal range of the chord height and the angle control can be quickly found by using PSO algorithm. Aiming at the collapse problem in the laser cladding process, a robot cladding path optimization method based on the layer path interpolation is proposed. A four-layer path interpolation simulation and the contrast experiments before and after the path optimization are completed; the results show that the robot cladding path optimization method can solve the problem of the collapse in laser cladding.

Practical implications

Robot cladding path optimization is one of the key technologies of LCF, and the quality of the robot cladding path is affected by STL model error and the path optimization method. This paper proposed a robot cladding path optimization method for LCF. This method can be used in other additive manufacturing techniques.

Originality/value

The quality of cladding path is important for LCF; this paper first proposed the optimization method of the robot cladding path for LCF to solve the collapse problem.

Citation

Zheng, H., Cong, M., Liu, D., Dong, H. and Liu, Y. (2019), "Robot path optimization for laser cladding forming", Industrial Robot, Vol. 46 No. 2, pp. 281-289. https://doi.org/10.1108/IR-07-2018-0148