Risk and reliability assessment about a manufacturing issue in a power MOSFET for automotive applications

Bergès, Corinne; Soufflet, Pierre; Jadrani, Abdeslam

doi:10.1016/j.microrel.2014.07.022

Cited by 4 publications

(1 citation statement)

References 4 publications

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“…Scholars Domen Tabernik et al [7] proposed a two-stage method based on SSD network, which can still conduct training and learning in relatively few data sets and obtain better results. Scholars Wang et al [8] designed a multiscale segmentation network based on U-Net architecture, including an atrous spatial pyramid pooling (ASPP) module and an inception module. This method can detect various types of subway tunnel defects.…”

Section: Introductionmentioning

confidence: 99%

Defect detection algorithm of lightweight chip based on improved YOLOv5s

Chen,

Yao,

Jiang

et al. 2023

International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023)

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Section: Introductionmentioning

confidence: 99%

Defect detection algorithm of lightweight chip based on improved YOLOv5s

Chen,

Yao,

Jiang

et al. 2023

International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023)

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Accelerated life testing for reliability improvement: a case study on Moulded Case Circuit Breaker (MCCB) mechanism

Rane¹,

Potdar

Rane

2019

Int J Syst Assur Eng Manag

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Deep Learning-Based Integrated Circuit Surface Defect Detection: Addressing Information Density Imbalance for Industrial Application

Wang,

Gao,

Guo

et al. 2024

Int J Comput Intell Syst

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In this study, we aimed to address the primary challenges encountered in industrial integrated circuit (IC) surface defect detection, particularly focusing on the imbalance in information density arising from difficulties in data sample collection. To this end, we have developed a new hybrid architecture model for IC surface defect detection (SDDM), based on ResNet and Vision Transformer (ViT). The core innovation of SDDM lies in the integration of the concepts of image information density and dataset information density, effectively identifying and processing areas of high information density through multi-channel image segmentation techniques. The convolution operations performed within each patch of the model help to precisely capture positional information, thereby meticulously differentiating the complex details on the surface defect detection of ICs. We optimized the model to make it more suitable for industrial applications, significantly reducing computational and operational costs. The experimental results confirmed that the improved SDDM model achieved an accuracy rate of 98.6% on datasets with uneven information density, effectively enhancing the productivity of IC packaging and testing companies, particularly in handling datasets with imbalanced information density.

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Risk and reliability assessment about a manufacturing issue in a power MOSFET for automotive applications

Cited by 4 publications

References 4 publications

Defect detection algorithm of lightweight chip based on improved YOLOv5s

Defect detection algorithm of lightweight chip based on improved YOLOv5s

Accelerated life testing for reliability improvement: a case study on Moulded Case Circuit Breaker (MCCB) mechanism

Deep Learning-Based Integrated Circuit Surface Defect Detection: Addressing Information Density Imbalance for Industrial Application

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