Technical Library | 2023-03-16 18:51:43.0
Conductive anodic filament (CAF) formation was first reported in 1976.1 This electrochemical failure mode of electronic substrates involves the growth of a copper containing filament subsurface along the epoxy-glass interface, from anode to cathode. Despite the projected lifetime reduction due to CAF, field failures were not identified in the 1980s. Recently, however, field failures of critical equipment have been reported.2 A thorough understanding of the nature of CAF is needed in order to prevent this catastrophic failure from affecting electronic assemblies in the future. Such an understanding requires a comprehensive evaluation of the factors that enhance CAF formation. These factors can be grouped into two types: (1) internal variables and (2) external influences. Internal variables include the composition of the circuit board material, and the conductor metallization and configuration (i.e. via to via, via to surface conductor or surface conductors to surface conductors). External influences can be due to (1) production and (2) storage and use. During production, the flux or hot air solder leveling (HASL) fluid choice, number and severity of temperature cycles, and the method of cleaning may influence CAF resistance. During storage and use, the principal concern is moisture uptake resulting from the ambient humidity. This paper will report on the relationship between these various factors and the formation of CAF. Specifically, we will explore the influences of printed wiring board (PWB) substrate choice as well as the influence of the soldering flux and HASL fluid choices. Due to the ever-increasing circuit density of electronic assemblies, CAF field failures are expected to increase unless careful attention is focused on material and processing choices.
Technical Library | 2021-06-07 19:06:32.0
The technological growth of the last decades has brought many improvements in daily life, but also concerns on how to deal with electronic waste. Electrical and electronic equipment waste is the fastest-growing rate in the industrialized world. One of the elements of electronic equipment is the printed circuit board (PCB) and almost every electronic equipment has a PCB inside it. While waste PCB (WPCB) recycling may result in the recovery of potentially precious materials and the reuse of some components, it is a challenging task because its composition diversity requires a cautious pre-processing stage to achieve optimal recycling outcomes. Our research focused on proposing a method to evaluate the economic feasibility of recycling integrated circuits (ICs) from WPCB. The proposed method can help decide whether to dismantle a separate WPCB before the physical or mechanical recycling process and consists of estimating the IC area from a WPCB, calculating the IC's weight using surface density, and estimating how much metal can be recovered by recycling those ICs. To estimate the IC area in a WPCB, we used a state-of-the-art object detection deep learning model (YOLO) and the PCB DSLR image dataset to detect the WPCB's ICs. Regarding IC detection, the best result was obtained with the partitioned analysis of each image through a sliding window, thus creating new images of smaller dimensions, reaching 86.77% mAP. As a final result, we estimate that the Deep PCB Dataset has a total of 1079.18 g of ICs, from which it would be possible to recover at least 909.94 g of metals and silicon elements from all WPCBs' ICs. Since there is a high variability in the compositions of WPCBs, it is possible to calculate the gross income for each WPCB and use it as a decision criterion for the type of pre-processing.
