Correlation Studies Between Laser Ultrasonic Inspection Data and Finite-Element Modeling Results in Evaluation of Solder Joint Quality in Microelectronic Packages

Reddy, Vishnu V. B.; Gupta, Saurabh; Williamson, Jaimal; Sitaraman, Suresh K.

doi:10.1115/1.4050898

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Post-processing analyses of SAW data has involved the use of signal processing methods such as local temporal coherence analysis [45], wavelet analysis [46], spectral analysis [47] in the frequency domain, and correlation coefficient analysis [48][49][50][51][52][53][54][55] in the time domain. Infrared thermography thermal images and transient temperature response have also been used to analyze heat conduction for defect detection in [56][57][58][59][60][61][62][63].…”

Section: Other Methodsmentioning

confidence: 99%

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A Survey of Detection Methods for Die Attachment and Wire Bonding Defects in Integrated Circuit Manufacturing

Alam

Kehtarnavaz

2022

IEEE Access

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Defect detection plays a vital role in the manufacturing process of integrated circuits (ICs). Die attachment and wire bonding are two steps of the manufacturing process that determine the power and signal transmission quality and dependability in an IC. This paper presents a survey or literature review of the methods used for detecting these defects based on different sensing modalities used including optical, radiological, acoustical, and infrared thermography. A discussion of the detection methods used is provided in this survey. Both conventional and deep learning approaches for detecting die attachment and wire bonding defects are considered along with challenges and future research directions.INDEX TERMS die attachment and wire bonding defects, defect detection in IC manufacturing, integrated circuit (IC) defects

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Section: Other Methodsmentioning

confidence: 99%

“…SAW has been used to identify defects such as missing bumps and cracks in [45][46][47][48][49]50], voids in micro solder bumps in [54,55], underfills in [49], ball interconnections in flip chips and BGA in [51][52][53].…”

Section: Surface Acoustic Waves (Saw)mentioning

confidence: 99%

A Survey of Detection Methods for Die Attachment and Wire Bonding Defects in Integrated Circuit Manufacturing

Alam

Kehtarnavaz

2022

IEEE Access

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“…Ultrasonic detection can reveal defects in a less intuitive manner, and therefore, it often requires experienced inspectors to recognize and classify the type of defects. The X-ray detection method detects solder joint defects by the degree of energy attenuation of X-rays through the product (Reddy et al ., 2022). However, defects such as leakage welding cannot be detected by the X-ray detection method due to the weak absorption of X-rays by bubbles and cracks.…”

Section: Introductionmentioning

confidence: 99%

Robust vision detection of pipeline solder joints

An,

Kong

2024

SSMT

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Purpose Solder joint inspection plays a critical role in various industries, with a focus on integrated chip (IC) solder joints and metal surface welds. However, the detection of tubular solder joints has received relatively less attention. This paper aims to address the challenges of detecting small targets and complex environments by proposing a robust visual detection method for pipeline solder joints. The method is characterized by its simplicity, cost-effectiveness and ease of implementation. Design/methodology/approach A robust visual detection method based on the characteristics of pipeline solder joints is proposed. With the improved hue, saturation and value (HSV) color space, the method uses a multi-level template matching approach to first segment the pipeline from the background, and then match the endpoint of the pipeline to accurately locate the solder joint. The proposed method leverages the distinctive characteristics of pipeline solder joints and employs an enhanced HSV color space. A multi-level template matching approach is utilized to segment the pipeline from the background and accurately locate the solder joint by matching the pipeline endpoint. Findings The experimental results demonstrate the effectiveness of the proposed solder joint detection method in practical detection tasks. The average precision of pipeline weld joint localization exceeds 95%, while the average recall is greater than 90%. These findings highlight the applicability of the method to pipeline solder joint detection tasks, specifically in the context of production lines for refrigeration equipment. Research limitations/implications The precision of the method is influenced by the placement angle and lighting conditions of the test specimen, which may pose challenges and impact the algorithm's performance. Potential avenues for improvement include exploring deep learning methods, incorporating additional features and contextual information for localization, and utilizing advanced image enhancement techniques to improve image quality. Originality/value The proposed pipeline solder joint detection method offers a novel and practical approach. The simplicity, cost-effectiveness and ease of implementation make it an attractive choice for detecting pipeline solder joints in different industrial applications.

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Discriminative non-destructive imaging of flip chips based on photoacoustic remote sensing microscopy with layered elasto-optic models

Chen,

Ding,

et al. 2024

Opt. Express

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Discriminative internal imaging for different chip layers can pinpoint the location of critical defect in the flip chips, yet existing methods face challenges in in-line imaging to identify defects or structures from the sub-surface within the silicon substrate and their underlying coating. To address these challenges, we develop and verify layered elasto-optic models for photoacoustic remote sensing microscopy (PARS) that distinguish structures from multi-layers within a single device for in-line flip-chip wafer inspection. A finite-difference time-domain algorithm based on transparent source (TS-FDTD) accurately predicts different initial slopes of PARS signals within the silicon-metal and the silicon-air models. The initial slopes of PARS signals are experimentally validated and utilized for discriminative non-destructive imaging of the interdigital electrode chips and silicon cracks within the same region of interest. PARS with layered elasto-optic models and non-contact fast scanning has the potential for in-line detection of defects from various layered structures with different refractive indices, offering an approach for discriminative non-destructive testing (NDT) of flip-chip and layered structures.

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Correlation Studies Between Laser Ultrasonic Inspection Data and Finite-Element Modeling Results in Evaluation of Solder Joint Quality in Microelectronic Packages

Cited by 3 publications

References 6 publications

A Survey of Detection Methods for Die Attachment and Wire Bonding Defects in Integrated Circuit Manufacturing

A Survey of Detection Methods for Die Attachment and Wire Bonding Defects in Integrated Circuit Manufacturing

Robust vision detection of pipeline solder joints

Discriminative non-destructive imaging of flip chips based on photoacoustic remote sensing microscopy with layered elasto-optic models

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