Mr. Manuel Zimmermann Profile

Manuel Zimmermann

at GÖPEL electronic GmbH

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Publications (2)

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Proceedings Article | 21 June 2019 Paper

Optical inspection of noncooperative copper surface structures using multi- and hyperspectral acquisition systems

Markus Wrieden, Andreas Breitbarth, Manuel Zimmermann, Jörg Schambach, Maik Rosenberger, Gunther Notni

Proceedings Volume 11061, 1106106 (2019) https://doi.org/10.1117/12.2525734

KEYWORDS: Optical filters, Cameras, Imaging systems, Inspection, Image filtering, Copper, Sensors, Bandpass filters, 3D metrology

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In order to enhance the efficiency of quality inspection of Direct Copper Bonded (DCB) structures an optical inspection using a 3D measuring system is conceivable. However, it is a challenging task to use 3D optical measurement techniques for diffuse reflective copper surfaces. This work deals with the optical detection of defects of the copper surface, using multi- and hyperspectral acquisition devices. Over a broad spectral range from the visual spectrum to the short-wave infrared (400 nm - 1700 nm) it is analysed which wavelengths provide good contrast ratios for the detection of flaws. For the inspection of the sample back side, the push-broom imager, operating in the VIS and NIR range (400 nm - 1000 nm), provides the best contrast ratio. An outstanding contrast is reached around 400 nm. Deposited particles on the front side of the DCB substrates are best detected by the filter wheel camera, which is sensitive in the visual and near infrared range. Outstanding contrast is reached with wavelengths around 640 nm. After evaluating the standard deviations of the gray values, it can be shown that defects differ clearly from flawless substrate areas under investigation with light of wavelengths 577 nm, 640 nm and 950 nm. Furthermore, the comparison between certain pixel spectra confirms that significant differences appear at the same three wavelengths. Regarding an automated inspection of defects, it is advisable to shift the pattern projection for the 3D correspondence analysis to the spectral ranges mentioned.

Proceedings Article | 26 June 2017 Paper

Verification of real sensor motion for a high-dynamic 3D measurement inspection system

Andreas Breitbarth, Martin Correns, Manuel Zimmermann, Chen Zhang, Maik Rosenberger, Jörg Schambach, Gunther Notni

Proceedings Volume 10329, 103290O (2017) https://doi.org/10.1117/12.2270288

KEYWORDS: 3D metrology, Motion measurement, Sensors, Inspection, Motion estimation, Optical inspection, Imaging systems, 3D image processing, Solids

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Inline three-dimensional measurements are a growing part of optical inspection. Considering increasing production capacities and economic aspects, dynamic measurements under motion are inescapable. Using a sequence of different pattern, like it is generally done in fringe projection systems, relative movements of the measurement object with respect to the 3d sensor between the images of one pattern sequence have to be compensated.

Based on the application of fully automated optical inspection of circuit boards at an assembly line, the knowledge of the relative speed of movement between the measurement object and the 3d sensor system should be used inside the algorithms of motion compensation. Optimally, this relative speed is constant over the whole measurement process and consists of only one motion direction to avoid sensor vibrations. The quantified evaluation of this two assumptions and the error impact on the 3d accuracy are content of the research project described by this paper.

For our experiments we use a glass etalon with non-transparent circles and transmitted light. Focused on the circle borders, this is one of the most reliable methods to determine subpixel positions using a couple of searching rays. The intersection point of all rays characterize the center of each circle. Based on these circle centers determined with a precision of approximately 1=50 pixel, the motion vector between two images could be calculated and compared with the input motion vector. Overall, the results are used to optimize the weight distribution of the 3d sensor head and reduce non-uniformly vibrations. Finally, there exists a dynamic 3d measurement system with an error of motion vectors about 4 micrometer. Based on this outcome, simulations result in a 3d standard deviation at planar object regions of 6 micrometers. The same system yields a 3d standard deviation of 9 µm without the optimization of weight distribution.

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