Sustainability Analysis of a ZnO-NaCl-Based Capacitor Using Accelerated Life Testing and an Intelligent Modeling Approach

From small toys to satellites, capacitors play a vital role as an energy storage element, filtering or controlling other critical tasks. This research paper focuses on estimating the remaining useful life of nanocomposite-based fabricated capacitor using various experimental and artificial intelligence techniques. Accelerated testing is used explore sustainability capacitor. The acceleration factors affecting health are investigated, experiments designed Taguchi’s approach. lifetime calculated statistical technique, i.e., regression analysis Minitab 18.1 software. An expert model neural networks (ANN), which warns user any upcoming faults failures. average capacitor, accelerated testing, regression, network, reported 13,724.3 h, 14,515.9 14,247.1 respectively. A comparison conducted, performance metrics analyzed opt for most efficient technique prediction confirms 93.83% accuracy method 95.82% networks. root mean square error (RMSE) found be 0.102 0.167, respectively, validates consistency reliability methods.