Intelligent X-ray inspection for quality control of solder joints

Neubauer, C.

doi:10.1109/3476.622881

Cited by 55 publications

(16 citation statements)

References 13 publications

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“…[1][2][3][4] However, attempts to extend this technique to include both component and PCB analysis have not yet resulted in success due primarily to a lack of image analysis software. Automatic defect recognition methods have employed such techniques as image subtraction, image comparison overlays and image measurements.…”

Section: Fault Detectionmentioning

confidence: 99%

Fault detection and visualization through micron-resolution X-ray imaging

Cicchiani

Hartmuller

Sell

et al. 2008

2008 Ieee Autotestcon

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This paper describes a novel, non-intrusive method for the detection of faults within printed circuit boards (PCBs) and their components using digital imaging and image analysis techniques. High-resolution X-ray imaging systems provide a means to detect and analyze failures and degradations down to micron-levels both within the PCB itself and the components that populate the board. Further, software tools can aid in the analysis of circuit features to determine whether a failure has occurred, and to obtain positive visual confirmation that a failure has occurred. Many PCB and component failures previously undetectable through today's test methodologies are now detectable using this approach.

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Section: Fault Detectionmentioning

confidence: 99%

Fault detection and visualization through micron-resolution X-ray imaging

Cicchiani

Hartmuller

Sell

et al. 2008

2008 Ieee Autotestcon

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“…X -ray imaging is a well-known method of nondestructive inspection in industry; in electronics, it is used mainly for detection of defects in solder joints, especially under BGA packages [1,2]. However, preexisting literature on the subject of x-ray imaging of LTCC remains scarce [3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

X-Ray Inspection of LTCC Devices: Theory and Practice

Zaraska¹,

Gaudyn²,

Bienńkowski³

et al. 2011

Journal of Microelectronics and Electronic Packaging

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AbstractÀThe appeal of the LTCC (low temperature cofired ceramic) process lies in the possibility of creating multilayer (3D) structures, integrating conductor paths between passive elements, such as inductors, resistors, and resonance cavities. Unfortunately, the very nature of a cofired device makes postfiring optical inspection of buried elements impossible, as the ceramic material is opaque to visible light. This limitation, however, does not exist at x-ray wavelengths. The aim of this paper is to provide a practical overview of the application of high resolution x-ray imaging for nondestructive inspection and fault detection in multilayer LTCC structures. First, we present a simplified mathematical description of x-ray absorption inside an LTCC structure and demonstrate that due to the physical properties of the substrate (glass/Al 2 O 3 ceramic), the conductor material (silver), and the cavity fill (air), a high contrast image of the investigated structure can be obtained. Next, we show the application of a commercial off the shelf industrial x-ray system for imaging various faults in LTCC structures, such as via voids (caused by inadequate filling of a via hole with conductor material), microcracks, paste creep (during lamination, excess via conductor leaks out of the via hole and in between the tape layers, shorting the via to an adjacent circuit), interruptions in conductor paths, and alignment errors. We also demonstrate the application of computed tomography to verify 3D geometry of buried resonance cavities and detect tape delaminations. Finally, we discuss the limitations of the method, related to structure thickness (number of layers), material composition, imaging geometry, and equipment characteristics, such as detector resolution and spatial noise.

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“…Tomography has a wide variety of applications, ranging from medical imaging to materials science [1,2,3,4,5]. In many of these applications, the object under investigation consists of only a few different materials, each corresponding to a particular gray level in the reconstructed image.…”

Section: Introductionmentioning

confidence: 99%

SDART: An algorithm for discrete tomography from noisy projections

Bleichrodt

Tabak

Batenburg

2014

Computer Vision and Image Understanding

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Computed tomography is a noninvasive technique for reconstructing an object from projection data. If the object consists of only a few materials, discrete tomography allows us to use prior knowledge of the gray values corresponding to these materials to improve the accuracy of the reconstruction. The Discrete Algebraic Reconstruction Technique (DART) is a reconstruction algorithm for discrete tomography. DART can result in accurate reconstructions, computed by iteratively refining the boundary of the object. However, this boundary update is not robust against noise and DART does not work well when confronted with high noise levels.In this paper we propose a modified DART algorithm, which imposes a set of soft constraints on the pixel values. The soft constraints allow noise to be spread across the whole image domain, proportional to these constraints, rather than across boundaries. The results of our numerical experiments show that SDART yields more accurate reconstructions, compared to DART, if the signal-to-noise ratio is low.

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Intelligent X-ray inspection for quality control of solder joints

Cited by 55 publications

References 13 publications

Fault detection and visualization through micron-resolution X-ray imaging

Fault detection and visualization through micron-resolution X-ray imaging

X-Ray Inspection of LTCC Devices: Theory and Practice

SDART: An algorithm for discrete tomography from noisy projections

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