Title: Analysis of common mould material organisation and mould life prediction algorithm based on machine vision

Authors: Maoqing Xie; Leigang Wang

Addresses: Hangzhou Polytechnic, Hangzhou 311402, Zhejiang, China ' School of Materials Science and Engineering, Jiangsu University, Zhenjiang 212013, Jiangshu, China

Abstract: The study addresses poor plasticity and toughness in steel plate forming by proposing a microstructure analysis and mould life prediction algorithm using machine vision. A distance sensor determines the forging edge, while a displacement sensor and industrial camera enhance measurement accuracy. The system utilises OpenCV to improve image processing speed and precision. A wear simulation for U-shaped hot forming moulds is developed using numerical methods to predict the effect of process parameters on wear depth and distribution. Results show that wear is most significant in the arc area, especially at the upper fillet, and the wear location shifts with increased forming cycles. The optimal superclosure value of 0.6 δ yields a 1.16% error between simulation and experimental results. The study concludes with an optimised wear model for predicting mould life, based on pin disk wear tests and finite element analysis.

Keywords: hot forming moulds; wear rate; image processing; mould lifespan; numerical simulation.

DOI: 10.1504/IJMPT.2025.147090

International Journal of Materials and Product Technology, 2025 Vol.70 No.1, pp.60 - 90

Received: 21 Jun 2024
Accepted: 19 Feb 2025
Published online: 10 Jul 2025 *

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