Compression Molding Mechanism and Parameter Evaluation of SiP

Lin, Yixuan; Hu, Ian; Chen, Dao-Long; Tarng, David; Hung, Chih-Pin

doi:10.1109/impact50485.2020.9268556

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Although wafer level packaging technology is well established in semiconductor industry but there are limited papers discuss about its application in LED. Process of wafer reconfiguration is the most practical application for LED [33][34][35][36]. The tested good chips are placed metal-up onto a carrier with adhesive tape.…”

Section: Molding Process For Cspmentioning

confidence: 99%

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A Review of Moldflow and Finite Element Analysis Simulation of Chip Scale Packaging (CSP) for Light Emitting Diode (LED)

Ching

Abdullah

2022

ARFMTS

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LED technology has been evolving aggressively in recent years from incandescent bulb during older days to as small as chip scale package. There is tremendous pressure to stay competitive in the market by optimizing products to next level of performance and reliability with shortest time to market. This changes the conventional way of product design and development to virtual prototyping by means of Computer Aided Engineering (CAE). The objective of the paper is to review challenges in chip scale packaging application in LED technology. The first part of the paper covered the literature survey of Chip Scale Packaging (CSP) in Light Emitting Diodes (LED), CSP architecture challenges, molding process and material for CSP. The findings of literature found that very few researchers had study silicone encapsulations process in CSP for LED in term of material characterization, mold process and simulation. Findings also shows that deployment Computational Fluid Dynamic (CFD) and integration of virtual prototyping using Finite Element Analysis (FEA) in product development in CSP for semiconductor industry had greatly reduced the time to market. However, there are very few papers discuss the application for CSP technology in LED industry. Second objective of the papers is discussion of methodolology in molding material characterization and simulation methodology. CFD helps to simulate the flow pattern of molding material as a function of different temperature, molding parameters settings for voids and displacement. FEA also help to evaluate the deformation of silicone in panel form and enable designer to predict the displacement of devices with different silicone.

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Section: Molding Process For Cspmentioning

confidence: 99%

“…Lin et al, [34] developed simulation molded underfill (MUF) using compression molding for SiP assembly process using Moldex3D software. In paper, authors apply Kamal's model to govern curing effects and Castro-Mascoko model to govern rheology characteristic of the EMC.…”

Section: Characterization Of Encapsulating Materials For Led and Elec...mentioning

confidence: 99%

A Review of Moldflow and Finite Element Analysis Simulation of Chip Scale Packaging (CSP) for Light Emitting Diode (LED)

Ching

Abdullah

2022

ARFMTS

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“…Technology has revolutionized our world and daily lives. For example, from wired phone to tting the cord and utilizes digital wireless technology connecting various [1,2]. The Smartphone technology is getting more compact to its handiest usage and size but packed with a powerful capability.…”

Section: Resin; Compression Mold; Resin Dispense; Compound; Granules mentioning

confidence: 99%

“Rey Resin Dispense Pattern” A Solution to Package Voids Defect on Thinner Package Thickness in Compression Mold

Belalo¹,

Arnido²

2021

JERR

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This paper will discuss how package voids Mold defect was addressed on thinner Compression mold packages like BGA (Ball Grid Array) and Sensor Devices. Significant action was the application of “Rey Resin Dispense” pattern in compression mold granule compound dispensing was a key action in reducing package voids defect. Using a DMAIC methodology (Define, Measure, Analyze, Improve and Control), a powerful analytical tool that serves as a guide towards the success of eliminating package voids defect. Using this methodology, all Key Process Input Variables (KPIVs) of compression mold and its molding compound material were identified as X’s or potential causes and test its significance to affect Y-response which is the package voids. Funneling of X’s further trimmed to the most possible contributor to package voids. The remaining possible contributor X’s undergo statistical validation which point to granule compound resin dispensing as the main contributor to induce package voids defect. Several actions were tried but failed to zero-out the defect. With the help of brainstorming and imaginative ideas and data gathered on how to improve granule resin dispense of compression mold positive outcome was realized. From the concept of light ray, to naming it as “Rey Resin Dispense” significantly reduce package voids defect in all thin BGA and Sensor devices. This learning was then applied to all existing thin packages and to new packages in compression molding process.

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