Transactions of Materials and Heat Treatment

Title：Layout for two-dimensional irregular sheet metal parts based on BL-NFP neural network algorithm

Authors： Liu Lingling Zhao Fu Gong Yanjue

Unit： Institute of Artificial Intelligence Beijing University of Industry and Commerce

KeyWords： two dimensional irregular sheet metal parts energy function BL-NFP neural network algorithm layout utilization rate of material

ClassificationCode：TH164

year,vol(issue):pagenumber：2021,46(12):54-60

Abstract：

For the problems of low utilization rate and long calculation time of two-dimensional irregular sheet metal parts in traditional industrial production, a BL-NFP (Bottom Left-No Fit Polygon) neural network algorithm with energy function as the carrier was proposed, which combined BL (Bottom-Left) positioning algorithm with the geometric characteristics of critical polygon (No-Fit Polygon, NFP), and the layout process of sheet metal parts was simulated. Then, the method of calculating the area sizes of the parts to be placed first,and then placing the objects to be arranged was adopted. Furthermore, the output data of the algorithm and the data results listed by the predecessors were tested and compared by Matlab. The results show that BL positioning algorithm can reasonably calculate the placing position of parts, NFP can effectively solve the problem of low layout utilization rate for irregular parts, and the neural network algorithm can effectively improve the solution speed. Aiming at the layout problem of two-dimensional irregular sheet metal parts, compared with the traditional neural network algorithm, the time of the optimal solution calculated by blanking machine of sheet metal parts is shortened by 40% using this algorithm, and the utilization rate of sheet metal material is improved about 8%.

Funds：

国家自然科学基金资助项目（51975006）

作者简介：刘玲玲（1995-），女，硕士研究生 E-mail：137757301@qq.com 通信作者：赵罘（1972-），男，博士，副教授 E-mail：zhaof@btbu.edu.cn

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