A New Fan-Out Package Structure Utilizing the Self-Alignment Effect of Molten Solder to Improve the Die Shift and Enhance the Thermal Properties

Park, Hwan-Pil; Park, Jae Yong; Seo, Gwancheol; Kim, Young‐Ho

doi:10.1109/ectc.2017.148

Cited by 5 publications

(1 citation statement)

References 19 publications

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“…Many research papers dealt with the self-alignment of passive components and of highly integrated packages. Park et al (2017) proposed a new process for improving the selfalignment ability of fan-out packages. They found that the selfalignment of these packages can be enhanced by using backsided under bump metallisation on the rear side of semiconductor devices.…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based prediction of component self-alignment in vapour phase and infrared soldering

Krammer

Martinek

Illés

et al. 2019

SSMT

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Purpose This paper aims to investigate the self-alignment of 0603 size (1.5 × 0.75 mm) chip resistors, which were soldered by infrared or vapour phase soldering. The results were used for establishing an artificial neural network for predicting the component movement during the soldering. Design/methodology/approach The components were soldered onto an FR4 testboard, which was designed to facilitate the measuring of the position of the components both prior to and after the soldering. A semi-automatic placement machine misplaced the components intentionally, and the self-alignment ability was determined for soldering techniques of both infrared and vapour phase soldering. An artificial neural network-based prediction method was established, which is able to predict the position of chip resistors after soldering as a function of component misplacement prior to soldering. Findings The results showed that the component can self-align from farer distances by using vapour phase method, even from relative misplacement of 50 per cent parallel to the shorter side of the component. Components can self-align from a relative misplacement only of 30 per cent by using infrared soldering method. The established artificial neural network can predict the component self-alignment with an approximately 10-20 per cent mean absolute error. Originality/value It was proven that the vapour phase soldering method is more stable from the component’s self-alignment point of view. Furthermore, machine learning-based predictors can be applied in the field of reflow soldering technology, and artificial neural networks can predict the component self-alignment with an appropriately low error.

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Section: Introductionmentioning

confidence: 99%