Reliability analysis for a dynamic k-out-of-n system with thermal balance control

Thermal failures, often caused by localized high temperatures, are a pervasive and critical issue in system operations, significantly impacting reliability and performance. Optimizing the connection locations in dynamic systems presents a promising and effective measure to mitigate these failures. By strategically managing the spatial distribution of heat, it is possible to reduce localized high temperatures and enhance overall system reliability. However, this approach has been largely overlooked in existing research, leaving a gap in addressing thermal imbalance effectively. This study proposes a novel balance measure to quantify thermal balance. Compared to existing balancing systems, this is the first time that the spatial uniformity of performance distribution is considered. The balance measure can help the system maintain thermal balance while meeting dynamic demands, thereby reducing thermal failures and improving system reliability. In addition, the thermal balance was incorporated for the first time in studies of dynamic k-out-of-n models with a failure threshold modeled by a random process. To address the system's complexity, we develop a reliability assessment method based on Monte Carlo simulation and solve a redundancy allocation problem to minimize system volume while meeting reliability constraints. Numerical examples demonstrate the effectiveness of our approach, showcasing its practical applicability and impact.