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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOP Conference Series: Materials Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
