Electronic part manufacturers often provide reliability values in metrics such as Mean Time Between Failures (MTBF) and its inverse, Failures in Time (FIT). These metrics assume a constant failure rate and do not account for damage accumulation or wear-out phenomena, making the part selection and management based on this information meaningless.This thesis will report on the challenges associated with manufacturers' avoidance of sharing critical part information and how insufficient information hampers decision-making for part selection. The thesis uses four die-level failure mechanisms (Electromigration, Time-Dependent Dielectric Breakdown, Hot Carrier Injection, and Negative Bias Temperature Instability) as demonstration cases. It investigates the extent to which industry-published documents can be used to obtain the data necessary to simulate these mechanisms. It will report on methods of selecting an appropriate failure model based on the part technology level and identifying the required parameters for estimating the part's time to failure. Various scattered part information sources, literature, and industry-published documents may include the input parameters of failure models. The thesis provides insights into the complexity of understanding these information sources and various methods to obtain the required parameters to estimate the time to failure distributions. The methodology considers the susceptibility of parts to die-level failure mechanisms and compares components for reliability. A simulation template that facilitates practical implementation by enabling designers, engineers, and procurement teams to make informed decisions while selecting electronic parts for specific applications is introduced. The research findings and methodology presented provide valuable insights for users to improve the reliability and performance of electronic systems through effective part selection.