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Detection of production relevant deviations in paint sprays.

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Title: Detection of production relevant deviations in paint sprays.
Authors: Tiedje, Oliver1 (AUTHOR) oliver.tiedje@ipa.fraunhofer.de, Paustian, Stephan1 (AUTHOR) stephan.paustian@ipa.fraunhofer.de, Rosenkranz, Simon2 (AUTHOR) sr@aom-systems.com, Hecker, Meiko2 (AUTHOR) mh@aom-systems.com, Tropea, Cameron3 (AUTHOR) ctropea@sla.tu-darmstadt.de
Source: Journal of Coatings Technology & Research. May2025, Vol. 22 Issue 3, p877-884. 8p.
Subjects: Spray painting, Electrostatic fields, Air flow, Turbulent flow, Turbulence
Abstract: Spray painting is still a poorly manageable process due to the complex interaction of physical, chemical and environmental influences like turbulent air flows, strong electrostatic fields, complex viscosity of paints and paint booth conditions. Consequently, many important properties of the painted film, like thickness, color, surface structure and the efficiency of the process are not controllable in an adequate manner, despite the enormous economic ramifications of poor quality control in high volume applications, such as in the automotive industry. This study shows how novel, online spray monitoring can instantaneously generate characterizing quantities from the spray to detect harmful deviations in the process. In this study, several minute changes have been experimentally imposed on a paint system, such as changed paint viscosity or pigmentation, deviations in air flow and paint flow rates, and defective or used and worn equipment parts. It will be shown that all these deviations lead to features which allow a clear distinction from the intact and reference cases. Additionally, it is shown that most of the deviations, if not detected, would have led to quality issues of the paint coating. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Coatings Technology & Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Detection of production relevant deviations in paint sprays.
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  Data: <searchLink fieldCode="AR" term="%22Tiedje%2C+Oliver%22">Tiedje, Oliver</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> oliver.tiedje@ipa.fraunhofer.de</i><br /><searchLink fieldCode="AR" term="%22Paustian%2C+Stephan%22">Paustian, Stephan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> stephan.paustian@ipa.fraunhofer.de</i><br /><searchLink fieldCode="AR" term="%22Rosenkranz%2C+Simon%22">Rosenkranz, Simon</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> sr@aom-systems.com</i><br /><searchLink fieldCode="AR" term="%22Hecker%2C+Meiko%22">Hecker, Meiko</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> mh@aom-systems.com</i><br /><searchLink fieldCode="AR" term="%22Tropea%2C+Cameron%22">Tropea, Cameron</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> ctropea@sla.tu-darmstadt.de</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Coatings+Technology+%26+Research%22">Journal of Coatings Technology & Research</searchLink>. May2025, Vol. 22 Issue 3, p877-884. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Spray+painting%22">Spray painting</searchLink><br /><searchLink fieldCode="DE" term="%22Electrostatic+fields%22">Electrostatic fields</searchLink><br /><searchLink fieldCode="DE" term="%22Air+flow%22">Air flow</searchLink><br /><searchLink fieldCode="DE" term="%22Turbulent+flow%22">Turbulent flow</searchLink><br /><searchLink fieldCode="DE" term="%22Turbulence%22">Turbulence</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Spray painting is still a poorly manageable process due to the complex interaction of physical, chemical and environmental influences like turbulent air flows, strong electrostatic fields, complex viscosity of paints and paint booth conditions. Consequently, many important properties of the painted film, like thickness, color, surface structure and the efficiency of the process are not controllable in an adequate manner, despite the enormous economic ramifications of poor quality control in high volume applications, such as in the automotive industry. This study shows how novel, online spray monitoring can instantaneously generate characterizing quantities from the spray to detect harmful deviations in the process. In this study, several minute changes have been experimentally imposed on a paint system, such as changed paint viscosity or pigmentation, deviations in air flow and paint flow rates, and defective or used and worn equipment parts. It will be shown that all these deviations lead to features which allow a clear distinction from the intact and reference cases. Additionally, it is shown that most of the deviations, if not detected, would have led to quality issues of the paint coating. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Coatings Technology & Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11998-024-01015-1
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        Text: English
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        Type: general
      – SubjectFull: Electrostatic fields
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      – SubjectFull: Air flow
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      – SubjectFull: Turbulent flow
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              M: 05
              Text: May2025
              Type: published
              Y: 2025
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