Approach of a physically based lifetime model for solder layers in power modules

Steinhorst, Peter; Poller, Tilo; Lutz, Josef

doi:10.1016/j.microrel.2013.07.094

Cited by 17 publications

(6 citation statements)

References 4 publications

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“…Simulation-based power cycling and lifetime prediction is another emerging approach, that has grabbed the attention of many research groups [21,88,128,[141][142]. In this approach, physics-based models are required to represent various deformation mechanisms.…”

Section: Summary and Discussion On Challenges And Trendsmentioning

confidence: 99%

A Review on IGBT Module Failure Modes and Lifetime Testing

2021

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Section: Summary and Discussion On Challenges And Trendsmentioning

confidence: 99%

A Review on IGBT Module Failure Modes and Lifetime Testing

2021

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“…The failure of the power device packaging caused by the temperature cycle is related to the volume average inelastic working energy density (W ), which can be described by the Darveaux model [18], [19] as follows:…”

Section: Thermomechanical Stress Modelingmentioning

confidence: 99%

Thermomechanical Oriented Reliability Enhancement of Si MOSFET Panel-Level Packaging Fusing Ant Colony Optimization With Backpropagation Neural Network

Jiang

Chen

Qian

et al. 2023

IEEE Trans. Compon., Packag. Manufact. Technol.

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Considerable advancements in power semiconductor devices have resulted in such devices being increasingly adopted in applications of energy generation, conversion, and transmission. Hence, we proposed a fan-out panel-level packaging (FOPLP) design for 30-V Si-based metal-oxidesemiconductor field-effect transistor (MOSFET). To achieve superior reliability of packaging, we applied the nondominated sorting genetic algorithm with elitist strategy (NSGA-II) and ant colony optimization-backpropagation neural network (ACO-BPNN) to optimize the design of redistribution layer (RDL) in FOPLP. We first quantified the thermal resistance and thermomechanical coupling stress of the designed package under thermal cycling loading. Next, NSGA-II and ACO-BPNN were used to optimize the size of the RDL blind via. Finally, the effectiveness of the proposed reliability optimization methods was verified by performing thermal shock reliability aging tests on the prepared devices.

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“…Many physical models have been proposed so far to tackle the existing challenges on reliability assessment of solder joints 6 – 9 . A wide range of factors including the fundamental mechanical properties, thermal variations, intermetallic formation, phase transition and defects nucleation have been investigated to predict the probability that the solder interconnection renders an appropriate mechanical and physical behavior in a specific timespan with no failure 10 – 12 . For instance, great works have been carried out to capture a broad range of temperature and strain rate in the constitutive models 13 , 14 .…”

Section: Introductionmentioning

confidence: 99%

Correlation-driven machine learning for accelerated reliability assessment of solder joints in electronics

Samavatian

Fotuhi‐Firuzabad

Samavatian

et al. 2020

Sci Rep

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The quantity and variety of parameters involved in the failure evolutions in solder joints under a thermo-mechanical process directs the reliability assessment of electronic devices to be frustratingly slow and expensive. To tackle this challenge, we develop a novel machine learning framework for reliability assessment of solder joints in electronic systems; we propose a correlation-driven neural network model that predicts the useful lifetime based on the materials properties, device configuration, and thermal cycling variations. The results indicate a high accuracy of the prediction model in the shortest possible time. A case study will evaluate the role of solder material and the joint thickness on the reliability of electronic devices; we will illustrate that the thermal cycling variations strongly determine the type of damage evolution, i.e., the creep or fatigue, during the operation. We will also demonstrate how an optimal selection of the solder thickness balances the damage types and considerably improves the useful lifetime. The established framework will set the stage for further exploration of electronic materials processing and offer a potential roadmap for new developments of such materials.

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Approach of a physically based lifetime model for solder layers in power modules

Cited by 17 publications

References 4 publications

A Review on IGBT Module Failure Modes and Lifetime Testing

A Review on IGBT Module Failure Modes and Lifetime Testing

Thermomechanical Oriented Reliability Enhancement of Si MOSFET Panel-Level Packaging Fusing Ant Colony Optimization With Backpropagation Neural Network

Correlation-driven machine learning for accelerated reliability assessment of solder joints in electronics

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