Sindhu, Tabassum NazÇolak, Andaç BaturLone, Showkat AhmadShafiq, Anum2023-06-232023-06-232023https://hdl.handle.net/11467/6670https://doi.org/10.1002/qre.3352The investigation of lifetime reliability analysis is vital for confirming the quality of devices, equipment, electronic tube flops, and so forth. Statistical investigators have become more interested in lifetime model exploration in recent years, particularly in the last decade, without considering the issue of modeling the metrics of model reliability using artificial neural networks (ANNs). This study addresses this vacuum by discussing the multilayer ANN with Bayesian regularization modeling for reliability metrics of generalized exponential model based on inverse power law (IPL). The numerical findings of the reliability investigations and the values obtained from the ANN have been examined and analyzed carefully. The findings show that ANNs are a powerful and useful mathematical tool for analyzing the reliability of lifetime model based on IPL. Finally, a real life framework is implemented that support the theory of a research study.eninfo:eu-repo/semantics/embargoedAccessartificial neural network; mean inactivity time; mean residual life; mean time to failure; reliability functionArticleQ2WOS:000972508300001N/A2-s2.0-8515295719310.1002/qre.3352