TY - JOUR

T1 - Improving the surface quality of AlMgSi1 alloy with the selection of the appropriate vibration grinding stones

AU - Engler, Carsten

AU - Georgiadis, Anthimos

AU - Lange, Dirk

AU - Meier, Nicolas

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2024/12

Y1 - 2024/12

N2 - The number and variety of paints and coating systems in the automotive industry have increased in recent years. However, the basic requirement for the quality of the paints still depends on the surfaces on which they are applied. This applies not only to the large body parts but also to all components that are integrated. There are many surface treatment processes and techniques that are used as an additional process step, such as pickling for a chemical surface treatment or blasting for a mechanical surface treatment. The present work investigates a method for optimizing the surface before painting, using the membrane cup of the ultrasonic sensor as an example for AlMgSi1 alloy, without implementing additional process steps. First, all process steps influencing the surface quality for the production of a membrane cup were considered for optimization. Then, based on a backward process chain analysis, vibratory grinding for deburring of the membrane cup was determined as the process step to be optimized. For the optimization of the vibratory grinding, experiments with two different grindstones were performed. For the characterization of the surface quality, the roughness parameters Rz and Ra were measured with a confocal laser scanning microscope and analyzed in order to determine the optimal process conditions. The experiments showed that the surface roughness can be significantly improved using dedicated process parameters and taking into account the geometry of the vibratory grinding stones. Moreover, different surface qualities can be achieved at different areas on the workpiece, this new approach provides a solution for surface optimization in various areas of the workpiece without additional process steps and costs.

AB - The number and variety of paints and coating systems in the automotive industry have increased in recent years. However, the basic requirement for the quality of the paints still depends on the surfaces on which they are applied. This applies not only to the large body parts but also to all components that are integrated. There are many surface treatment processes and techniques that are used as an additional process step, such as pickling for a chemical surface treatment or blasting for a mechanical surface treatment. The present work investigates a method for optimizing the surface before painting, using the membrane cup of the ultrasonic sensor as an example for AlMgSi1 alloy, without implementing additional process steps. First, all process steps influencing the surface quality for the production of a membrane cup were considered for optimization. Then, based on a backward process chain analysis, vibratory grinding for deburring of the membrane cup was determined as the process step to be optimized. For the optimization of the vibratory grinding, experiments with two different grindstones were performed. For the characterization of the surface quality, the roughness parameters Rz and Ra were measured with a confocal laser scanning microscope and analyzed in order to determine the optimal process conditions. The experiments showed that the surface roughness can be significantly improved using dedicated process parameters and taking into account the geometry of the vibratory grinding stones. Moreover, different surface qualities can be achieved at different areas on the workpiece, this new approach provides a solution for surface optimization in various areas of the workpiece without additional process steps and costs.

KW - Confocal laser scanning microscope

KW - Roughness

KW - Six sigma

KW - Surface optimization

KW - Vibration grinding

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85184837703&partnerID=8YFLogxK

UR - https://link.springer.com/journal/44147/volumes-and-issues

UR - https://jeas.springeropen.com/articles?query=&volume=71&searchType=&tab=keyword

UR - https://www.mendeley.com/catalogue/afd22256-a127-3ae1-a437-bc412d556e61/

U2 - 10.1186/s44147-023-00331-4

DO - 10.1186/s44147-023-00331-4

M3 - Journal articles

AN - SCOPUS:85184837703

VL - 71

JO - Journal of Engineering and Applied Science

JF - Journal of Engineering and Applied Science

SN - 1110-1903

IS - 1

M1 - 35

ER -