<p>Reliability analysis plays a crucial role in evaluating the performance and dependability of engineering and industrial systems. This research investigates how Semi-Markov process (SMP) can be used to evaluate reliability measures in a range of system configurations like series, parallel, bridge, <i>k</i>-out-of-<i>n</i> and mixed system. Semi-Markov techniques, in contrast to conventional Markov models, enable more generalized state-holding time distributions, which makes them ideal for real-world systems with non-exponential failure and repair times. The benefits of SMP in modelling complexities are highlighted along with important reliability indicators like availability, failure rates, and mean time to failure (MTTF). A brief overview of the use and advantages of this method is also provided in this study which also looks at actual applications, computational methods, and current advancements.</p>