Efficiency improvement in polycrystalline solar panel using thermal control water spraying cooling

Abstract: The increasing demand for electricity generated from main grids has necessitated the use of multiple microgrids, which serve as subsystems of the utility power. More recently, solar farms are being utilized for electricity generation, since solar irradiation is a green and sustainable renewable energy source. This energy source has witnessed high global growth figures, as more countries explore this alternative power source in the fourth industrial revolution. Solar panels are exposed to high temperatures due to the heat absorbed from the sun and this heat negatively impact its thermal control that lags its power generation. The excessive heat absorbed from the sun limits energy generated by the solar cells. Colling of solar panels is essential, especially on concentrated Photovoltaic (PV) systems. The paper focuses on an optimization option of an automated water spraying method that has effectively addressed a major gap experienced by the solar panel under hot weather conditions. The Introduction of a microcontroller-based thermal control water spraying system using an Arduino board was found to improve the efficiency of the solar cells. In the study, a solar collector cooling algorithm was designed and developed using a thermal control feedback system, which increased the efficiency of the solar panel array by 16.65%

Optimization of condition-based maintenance strategy prediction for aging automotive industrial equipment using FMEA

Abstract: Maintenance plays a highly important role in achieving production targets and system performance. Electromechanical equipment and facility infrastructure within motor manufacturing industries are expected to perform at optimal efficiency during the operational phase of production. A major problem in the automotive production plan from motor industry statistics is associated with unexpected downtime, which is largely linked to aging equipment. During production downtime, much time is lost to fault finding, repairs, and replacement of faulty components within production lines. This transforms into low throughput in production, and performance gradually declines during the operational life cycle of the equipment. This paper presents an approach taken to prevent such instances in the automotive manufacturing industry, which considers an optimized condition-based maintenance approach to predict the condition of each component and assembly line using Failure-Mode-and-Effect-Analysis (FMEA). The condition-based performance level prediction is designed to help in formulating maintenance schedules and strategies that eliminate unplanned downtimes