A Neural Network Model for Quality Prediction in the Automotive Industry

被引：1

作者：

Risan, Anders ^{[1
]}

Msakni, Mohamed Kais ^{[1
]}

Schutz, Peter ^{[1
]}

机构：

[1] Norwegian Univ Sci & Technol, Dept Ind Econ & Technol Management, N-7491 Trondheim, Norway

来源：

ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AND RESILIENT PRODUCTION SYSTEMS, PT V | 2021年 / 634卷

关键词：

Neural network; Quality control; Machine learning; Manufacturing;

D O I：

10.1007/978-3-030-85914-5_60

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present a machine learning application for the automotive industry. We study the use of neural networks to predict the location of milled holes in a bumper beam using historical measurement data. The overall goal of the study is to reduce the time needed for quality control procedures as the predictions can supplement manual control measurements. Our preliminary results indicate that the neural network can generally capture the production process variations, but underestimates larger deviations from the specified location.

引用

页码：567 / 575

页数：9

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