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Preventing Corrosion-related Failures in Electronic Assembly: A Multi-case Study Analysis

July 2023

Preventing Corrosion related Failures: Preventing Corrosion-related Failures in Electronic Assembly: A Multi-case Study Analysis


Preventing Corrosion related Failures: Corrosion is a prevalent failure mode in electronic products. The initiation of failure often stems from pre-existing corrosion contamination on soldering leads prior to assembly. This corrosion is further accelerated by environmental factors such as humidity, temperature, and acidity, ultimately leading to degradation of the board and failure during both post-assembly testing and the product’s lifespan.This study introduces a method that enables real-time and early detection of corrosion contamination on electronic components during the mounting process using pick-and-place technology.



Preventing Corrosion related Failures

The method utilizes the correlation between light reflectance from soldering leads during placement photography and the degree of corrosion present. Corroded leads possess a rougher surface and pitting spots which result in different light reflectance compared to pristine leads. This difference can be detected through AI forensic analysis of component images. The study presents an AI model that correlates lead finish with corrosion content and progression, and evaluates its performance on large-scale data. In this study, a real-world case is presented where corroded components were identified during the pick-and-place process. However, these components later failed during in-circuit testing (ICT).

Preventing Corrosion related Failures

Using scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDS) and cross-section analysis, the post-failure analysis verifies the accuracy of AI failure predictions on numerous components exhibiting corrosion during large-scale production. The proposed method has been implemented in multiple production lines, ensuring the inspection of all components without compromising throughput. It effectively identifies contaminated components that pose a safety risk. Rigorous testing has been conducted on over 3.5 billion components to validate the method’s efficacy.



Electronic components are the most expensive part of the Bill of Materials (BOM) and are also the most common cause of failures in electronic products. Nevertheless, traditional production methods don’t carry out systematic inspection, and seldom any tests are being made at all [1]. This is even though electronic components are the means of most of the failures in electronic products [2]. Unsafe components are more common today because of the electronic components shortage that has made the supply chain more complex and vulnerable to fraudulent falsifications [3]. As a result, components that were obtained from nonreliable sources, recycled components, components that were poorly stored, handled, or old components are more frequently used by the electronic industry. These components have a higher ratio of quality issues. The most dominant cause of the failure of aged components is corrosion propagation.

Preventing Corrosion related Failures

Various traditional methods are used to evaluate the solderability of electronic components [5]. In the defense industry, samples from batches of components suspected of poor solderability must be inspected in accordance with MILSTD-202, Method 208 [6] and SAE 26262 used in the automotive industry. These methods typically involve testing a small sample of components under specified conditions to assess the ability of the component leads to wet solder and the strength of the bond. However, this approach is based on the assumption that a small sample represents the entire batch, which is not always the case as demonstrated in [7]. Despite this, the impact of corrosion on soldering leads on product quality is often overlooked, despite the numerous studies and evidence on the effect of corrosion on bond strength and reliability [8]-[11]

Preventing Corrosion related Failures

In this study, we propose a method for detecting defective soldering leads on components during assembly [2], [12], [13]. The method allows for early detection of components with corrosion and contamination in the soldering leads during production, enabling their avoidance. Furthermore, we provide evidence of the method’s effectiveness by showcasing the correlation between failures caused by corrosion on components during assembly and field failure analysis cases. The inspection was carried out using data processed by Cybord.ai electronic component authentication and qualification software [14]. The software interfaces with the pick-and-place (PNP) machines during production and collects images of the components [15]. These images are then processed using a deep learning algorithm that searches for visual defects in the components and flags any suspected components [12], [16]. Additionally, another network is utilized to evaluate the texture of the soldering leads and estimate their solderability.

Preventing Corrosion related Failures

The method was applied to real assembled components. We present examples of electronic components VSON-12 Gate Drivers NexFET in 12-VSON-CLIP package (see Fig. 1), and QFN-12 Power switch (see Fig. 2) with corrosion that was detected by the presented method. The failure analysis of these components involved performing X-ray analysis, scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS) microscopy. Additionally, visible light microscopy was utilized in the analysis. The analysis establishes a correlation between the corrosion detected by AI and the and failure mode identified in analysis. The AI method was then calibrated to detect potential failures that may result in future failures.




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