Line heating process parameter forecasting method based on optimization concept

Abstract

In ship construction, line heating is a necessary process for forming ship plates with complex curvature. The determination of line heating process parameters has a significant impact on the accuracy of the process and the efficiency of shipbuilding. However, previous studies on this subject only stay at the level of predicting deformation, which has not meet the actual processing production requirements. In this paper, a new idea of forecasting line heating parameters proposed. Firstly, an Radial Basis Function (RBF) proxy model between processing parameters and deformation was constructed based on experimental data, and then the reliability of the proxy model is verified. The optimization objective for proxy model was set as the minimum difference between the final deformation and the target deformation. Meanwhile, an improved Multi-Objective Particle Swarm Optimization (MOPSO) method was employed to search the optimal-set of processing parameters with non-dominated solutions. The performance of the optimized parameter set was ranked by using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and the processing parameters combination ranking first was selected as the parameter forecasting result. The results showed that the predicted processing parameters have some reference for the practical engineering.