In Process Measurement Techniques Based on Available Sensors in the Stamping Machines for the Automotive Industry

We are currently going through an industrial period in which connectivity, data collection of the process and its understanding to optimize it is becoming more and more common. The automotive industry is no exception as we are on the way towards connected factories where the digitization of the stam...

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Bibliographic Details
Published in:Key engineering materials 2022-07, Vol.926, p.853-861
Main Authors: Peinado-Asensi, Ivan, Montes, Nicolas, García, E.
Format: Article
Language:English
Subjects:
Automobile industry
Data collection
Die drawing
Industrial development
Manufacturing
Measurement techniques
Mechanical components
Stamping
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Summary:We are currently going through an industrial period in which connectivity, data collection of the process and its understanding to optimize it is becoming more and more common. The automotive industry is no exception as we are on the way towards connected factories where the digitization of the stamping process is a trend followed by manufacturers. A common problem often encountered is the high cost required to develop solutions by using this technology. Obtaining parameters of the manufacturing process is a challenge on many occasions. New solutions have been proposed from an opposite point of view, i.e., we evaluate what information can be extracted from the equipment and from the data obtained we can bring forward the possible tools to be developed without the need for extra investment. This article shows the verification of an experimental process, previously developed, with which we intend to find out the status of the press during the drawing process for each cycle that is carried out during production and also the status of the equipment at all times, up to the point of detecting if there is any problem both in the die and in the mechanical components of the press and verifying it with the developed tool, showing that we can know the status of the equipment by monitoring the data in real time.
ISSN:1013-9826
1662-9795
1662-9795
DOI:10.4028/p-gvqkd4