高温计
冲压
统计过程控制
硬化(计算)
计算机科学
机械工程
质量保证
热成像
过程控制
生产线
材料科学
过程(计算)
温度测量
工程类
复合材料
光学
物理
图层(电子)
外部质量评估
红外线的
运营管理
操作系统
量子力学
作者
Eduard Garcia-Llamas,Jaume Pujante,Pol Torres,Francesc Bonada
出处
期刊:IOP conference series
[IOP Publishing]
日期:2021-06-01
卷期号:1157 (1): 012010-012010
被引量:8
标识
DOI:10.1088/1757-899x/1157/1/012010
摘要
Abstract The aim of this work is to investigate a simple on-line control methodology applicable to press hardening. Short production runs were performed in a laboratory plant, using a pyrometer to measure sheet and die temperatures with varying processing conditions. Sheets thus treated were studied in terms of microstructure and mechanical properties. Different closing die time and refrigeration conditions were employed to force OK and Not OK conditions. The experimental data including the process variables as a well as the resultant temperatures have been analysed and modelled by means of statistical analysis and Machine Learning algorithms, to discover hidden correlations that can lead to actionable predicting models. The results show a direct link of the final temperature with the microstructure and its hardness. The outcome of this paper can be used for efficient process design and detection of anomalous temperature meanwhile an industrial hot stamping process take part. In addition, the analysis performed can help productivity and quality assurance while leading towards a smarter and more efficient manufacturing scenario.
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