Intermittent failures and no fault found (NFF) phenomena are a concern in electronic systems because of their unpredictable nature and irregular occurrence. They can impose significant costs for companies, damage the reputation of a company, or be catastrophic in systems such as nuclear plants or avionics. Intermittent failures in systems can be attributed to hardware failures or software failures. In order to diagnose and mitigate the intermittent failures in systems, the nature and the root cause of these failures have to be understood. In this paper we have reviewed the current literature concerning intermittent failures and have a comprehensive study on how these failures happen, how to detect them and how to mitigate them.

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The rise of energy prices, concerns over climate change and geopolitical issues have brought special attention to renewable sources of energy and wind energy in particular. Based on NREL projections, the United States has more than 32,000 TWh of onshore and 17,000 TWh of offshore potential for wind power generation, which is far beyond its 11,000 TWh of current annual electricity consumption. However, there are a number of efficiency challenges that must be overcome in order to turn this potential into actual production. One area that can potentially improve the energy production of wind turbines is the correction of yaw error. Yaw error (also referred to as yaw angle or yaw misalignment) is the angle between the turbine’s rotor and the wind direction. A yaw error reduces turbine’s power production at wind speeds below the rated speed. Besides impacting the power producing ability of a turbine, yaw error also affects the reliability of critical subsystems in wind turbines. Variation in yaw error (at any wind speed and not only below the rated speed) affects the loads on the components and the subsequent mechanical stresses. These mechanical stresses change the damage accumulation for components and sub-assemblies, which ultimately affects their reliability. About 17 to 28% of wind project costs attribute to O&M costs, which are directly affected by the reliability. In this study, we investigate the effects of yaw error on the reliability of blades by performing load and stress analysis for various yaw errors. We then use the results of these analyses to adjust the Weibull parameters used for predicting the failure time of blades. Finally, we will use a stochastic cost model to show how correcting the yaw error can avoid maintenance costs in wind farms.