## 6 Conclusions  
We proposed a novel overload detection logic algorithm for DCSs, aimed at improving system stability and resource efficiency. While the algorithm showed promising results in simulation, it cannot yet be directly applied to legacy systems currently deployed at the Tae-An Thermoelectric Power Plant. However, the operating company has initiated investments in next-generation DCS technologies, anticipating future system upgrades. In preparation, we developed a simulation-based test bench to evaluate the algorithm's performance in advance of the new DCS installations. Future work will focus on developing an enhanced logic processor architecture and validating its effectiveness under realistic operational scenarios using this test environment. This paper presents an innovative and systematic approach to overload control and system reliability enhancement in DCS architectures, with particular emphasis on applications in thermoelectric power generation. The proposed real-time overload detection algorithm, when integrated with a modular MFP, demonstrates substantial improvements in fault resilience, load distribution, and computational efficiency. Analytical modeling and simulation-based validation confirm that the system effectively mitigates overload conditions and minimizes performance degradation in dynamically varying load environments. The algorithm's applicability to real-world thermoelectric plant operations was demonstrated through the simulation test bench, where it proactively managed critical system parameters, ensured efficient energy use, and reduced the likelihood of system failures. The modular test environment validated both the scalability and compatibility of the proposed solution, proving its adaptability to both existing infrastructures and future DCS platforms. Unlike conventional overload protection methods, the proposed system offers flexible integration with legacy systems while supporting the scalability needed for future expansion. Overall, the findings of this study highlight the potential of the proposed framework to contribute to the development of next-generation, self-regulating DCS architectures that address the growing demands of modern power grids. By delivering real-time fault detection, dynamic load balancing, and optimized resource allocation, the proposed solution enhances not only operational reliability and efficiency but also the sustainability of thermoelectric power plants. Based on the proposed hierarchical overload detection framework, future research can explore multi-objective optimization strategies that simultaneously balance CPU load, memory usage, and network traffic across distributed control segments. In addition, integrating this architecture with edge computing environments will enable \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Bench Marking Metric** & **FTAS** & **TUD** &
\begin{tabular}{c} **Proposed Method (NFP +** \\ **CFP + AFP**)** \\ \end{tabular} & **Improvement Rate** \\ \hline CPU Utilization (\%) & FTAS: 83.84 & TUD: 76.5 & 57.2 & +31.7\% \\ \hline Memory Usage (RAM, bytes) & CBLA: 338 & RLE: 296 & 260 & \(-\)23.1\% \\ \hline Execution Latency (\(\upmu\)s) & RLE-based: 300 & Symbol Table: 255 & 185 & \(-\)38.3\% \\ \hline ADC Comparator Count (8-bit) & Full-Flash: 255 & Subranged: 160 & 129 & \(-\)49.4\% \\ \hline ADC Power Consumption (8-bit, mW) & Full-Flash: 87.32 & Subranged: 87.32 & 87.32 & Same \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comprehensive benchmarking analysis comparing the proposed DCS architecture with two different architectures. low-latency, real-time decision-making closer to the physical system. These directions are expected to enhance scalability, responsiveness, and overall operational efficiency in large-scale industrial automation systems. While the current simulation setup replicates system behavior based on INFI-90 specifications and typical function code assignments from operational DCSs (e.g., Taean Power Plant), actual runtime data were not used due to confidentiality constraints.