<![CDATA[Turbine blades are critical components in a steam power plant that directly affect the thermal efficiency and reliability of the system. This study aims to conduct a systematic review of turbine blade design and failure using a systematic literature review (SLR) approach that covers four main classifications, namely Design and Optimization, Materials and Structural Analysis, Failure Analysis and Prediction, and Aerodynamics and Steam Flow. The results of the study show that blade design optimization using numerical methods such as Computational Fluid Dynamics (CFD), genetic algorithms, and the Taguchi method can significantly reduce energy losses, such as reducing condensation losses by up to 28.5% and reducing erosion rates by up to 58%. High-strength materials, such as Waspaloy, have proven effective for high-pressure applications, while surface hardening technologies such as laser hardening and shot peening increase the hardness and fatigue resistance of the blades. In addition, failure analysis using vibration techniques and the Metal Magnetic Memory (MMM) method allows early detection of damage to prevent major failures. This study concludes that the combination of multi-objective optimization techniques, real-time monitoring, and advanced material development can improve the energy efficiency and sustainability of steam power plants.]]>
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