@inbook{fbf76c7e66fb4ed99050f02f4b878158,
title = "Monitoring of the Flange Draw-In During Deep Drawing Processes Using a Thin-Film Inductive Sensor",
abstract = "The quality of deep-drawn parts is subject to uncontrollable fluctuations, triggered by material property variations and process deviations, which occur despite extensive quality controls along the entire process chain. Monitoring and controlling the draw-in of the sheet material—which is an indicator of a faultless deep drawing process—would allow for a significant increase in process robustness. However, this requires sensor systems suitable for the industrial environment, which so far do not exist. This paper presents a newly developed inductive sensor in thin-film technology for measuring the flange draw-in. The sensor was designed with the aid of finite-element-analysis and then manufactured using thin-film processes. After integration into a deep-drawing tool, the system was tested and validated. Afterwards, the detection of typical deep-drawing defects was investigated. It was demonstrated that the sensor system can reliably detect both cracks and wrinkles as well as the time at which they occur.",
keywords = "Deep drawing, Draw-in sensor, Inductive sensor, Process monitoring, Thin-film sensor",
author = "T. F{\"u}nfkirchler and M. Arndt and S. H{\"u}bner and F. Dencker and Wurz, \{M. C.\} and Behrens, \{B. A.\}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2023",
month = feb,
day = "2",
doi = "10.1007/978-3-031-18318-8\_12",
language = "English",
isbn = "978-3-031-18317-1",
series = "Lecture Notes in Production Engineering",
publisher = "Springer Nature",
pages = "111--121",
booktitle = "Lecture Notes in Production Engineering",
address = "United States",
}