Report
Machine learning for automated quality control in injection moulding manufacturing
| العنوان: | Machine learning for automated quality control in injection moulding manufacturing |
|---|---|
| المؤلفون: | Michiels, Steven, De Schryver, Cédric, Houthuys, Lynn, Vogeler, Frederik, Desplentere, Frederik |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Computer Science - Machine Learning |
| الوصف: | Machine learning (ML) may improve and automate quality control (QC) in injection moulding manufacturing. As the labelling of extensive, real-world process data is costly, however, the use of simulated process data may offer a first step towards a successful implementation. In this study, simulated data was used to develop a predictive model for the product quality of an injection moulded sorting container. The achieved accuracy, specificity and sensitivity on the test set was $99.4\%$, $99.7\%$ and $94.7\%$, respectively. This study thus shows the potential of ML towards automated QC in injection moulding and encourages the extension to ML models trained on real-world data. Comment: Accepted for publishing in ESANN conference proceedings 2022 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2206.15285 |
| رقم الانضمام: | edsarx.2206.15285 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |