Mapping rules and exchange methods for heterogeneous electronic parts libraries

2015 ◽  
Author(s):  
Katherine V. Whittington

Abstract The electronics supply chain is being increasingly infiltrated by non-authentic, counterfeit electronic parts, whose use poses a great risk to the integrity and quality of critical hardware. There is a wide range of counterfeit parts such as leads and body molds. The failure analyst has many tools that can be used to investigate counterfeit parts. The key is to follow an investigative path that makes sense for each scenario. External visual inspection is called for whenever the source of supply is questionable. Other methods include use of solvents, 3D measurement, X-ray fluorescence, C-mode scanning acoustic microscopy, thermal cycle testing, burn-in technique, and electrical testing. Awareness, vigilance, and effective investigations are the best defense against the threat of counterfeit parts.


2020 ◽  
Vol 96 (3s) ◽  
pp. 216-219
Author(s):  
И.П. Горбачев ◽  
Т.Ю. Корбанкова ◽  
А.Я. Кулибаба ◽  
А.А. Сашов

Показана нормативная документация, регламентирующая противодействие контрафакту и фальсификации в области электронной компонентной базы (ЭКБ). Приведены наиболее результативные методы исследования на предмет наличия признаков контрафактной ЭКБ. Отражены результаты исследований ЭКБ, снятой с производства, на предмет наличия признаков контрафактной продукции. Даны предложения по недопущению применения контрафактной ЭКБ. The article presents normative documentation for regulating counteraction to electronic parts counterfeiting and falsification. It highlights the most effective research methods of counterfeit electronic parts signs, offers the results of studies of counterfeit products signs in discontinued electronic parts and makes suggestions how to avoid counterfeit electronic parts.


Author(s):  
Yi-Chun Chen ◽  
Bo-Huei He ◽  
Shih-Sung Lin ◽  
Jonathan Hans Soeseno ◽  
Daniel Stanley Tan ◽  
...  

In this article, we discuss the backgrounds and technical details about several smart manufacturing projects in a tier-one electronics manufacturing facility. We devise a process to manage logistic forecast and inventory preparation for electronic parts using historical data and a recurrent neural network to achieve significant improvement over current methods. We present a system for automatically qualifying laptop software for mass production through computer vision and automation technology. The result is a reliable system that can save hundreds of man-years in the qualification process. Finally, we create a deep learning-based algorithm for visual inspection of product appearances, which requires significantly less defect training data compared to traditional approaches. For production needs, we design an automatic optical inspection machine suitable for our algorithm and process. We also discuss the issues for data collection and enabling smart manufacturing projects in a factory setting, where the projects operate on a delicate balance between process innovations and cost-saving measures.


2013 ◽  
Vol 770 ◽  
pp. 361-365
Author(s):  
Yu Peng Xin ◽  
Xi Tian Tian ◽  
Li Jiang Huang ◽  
Jun Hao Geng

In order to improve the efficiency of NC machining programming, and realize the rapid establishment of blank model or middle blank model, a geometrical modeling method of process driven by typical process model was put forward. This method is based on the typical process for the establishment of typical process model, to establish a mapping between modeling operation and machining process ontology, and format model mapping rules. In the process geometrical modeling of the high similarity parts, by calling the typical process model mapping rules, can generate process models automatically. A enterprise disc type parts typical process as an example is used to verify the proposed method.


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