Rajan Ambat

A printed circuit board (PCB) surface can fail by corrosion due to various environmental factors. This paper focuses on machine learning (ML) techniques to build predictive models to forecast PCB surface failure due to electrochemical migration (ECM) and leakage current (LC) levels under corrosive conditions containing the combination of six critical factors. The modeling methodology in this paper used common supervised ML algorithms by accomplishing significant evaluation metrics to show the performance of each algorithm. The conclusion of this study presents that ML algorithms can create predictive models to forecast PCB failures and estimate LC values effectively and quickly.

Electronic devices are exposed to a variety of climatic conditions worldwide. The day/night temperature fluctuations between the device interior and external conditions can lead to the formation of transient conditions within the enclosure that enhance the possibility of water layer build-up on the surface of Printed Circuit Board Assembly (PCBA). This paper deals with the parametric investigation of the effects assisting the formation of water film on PCBA surfaces under transient climatic conditions, which alters the functionality of electronic devices. Investigated parameters include the external humidity level, PCBA cleanliness, temperature difference between ambient and the PCBA, and the rate of temperature/humidity change. The effect of residues commonly associated with the soldering operations – weak organic acids – on the water film formation was investigated at 25°C/80%RH under isothermal and non-isothermal conditions. For non-isothermal conditions, the PCBA temperature was reduced to the level slightly above and below the dew point. The impact of external climate on wetting time of the contaminated PCBA was demonstrated by its exposure to day/night cyclic conditions and the overall effect on corrosion reliability of the electronic circuit was assessed. A combination of AC impedance and DC leakage current techniques was employed to determine the electrochemical changes of the PCBA surface resulting from the build-up of a conductive water film. The results show that the presence of hygroscopic flux residues increases the water vapour content above the surface leading to moisture condensation under potentially non-condensing conditions, and results in the corrosion reliability issues.