MARKOV MODEL ANALYSIS OF SYSTEM RELIABILITY AND SAFETY OF ELECTRONIC SYSTEMS

Abstract

The unexpected interruption of electronic systems is one of the most frequently occurring concerns, which may be related to safety issues and long durations of inactivity. This research focuses on evaluating the reliability and robustness of an elementary signal processing circuit, consisting of a capacitor, an NPN transistor, a resistor, and a diode, at an early stage of its design lifecycle. To fulfill this purpose, a continuous-time Markov model was developed, where a graphical representation of all possible states of the system, i.e., a transition diagram with 16 states, and mathematical equations were developed to calculate the overall failure rate and mean time between failures (MTBF) for the operational tenure of the system prior to failure.

Using failure rate data from a reputable source, i.e., the Military Reliability Handbook, four different component “Type” configurations within the circuit were evaluated. It was found that the Type 2 configuration performed better, with the lowest overall failure rate of 3.3675 x 10⁻⁴ per hour and the highest MTBF of about 2,970 hours, exceeding all other tested configurations. Thus, overall, this study concludes that Markov-based predictive modeling can be an effective tool to identify the most reliable combinations of components, helping designers make better-informed decisions and avoiding failures, which may lead to significant economic losses.