The increased deployment of renewable energy sources requires integration with conventional power plant to back-fill the inevitable dips in supply. This has meant that the cyclic loading on turbine blade components in conventional power plant has sharply increased (due to two-shifting and load following, producing many additional stop-start cycles). Condition-based monitoring/asset management and the use of appropriate (and validated) prediction tools in large scale turbine blades is required. A particular challenge for large steam turbine units is ensuring the integrity of the low pressure turbine last stage blades. Increased incidences of fatigue cracking in the root region of the turbine blades is seen due to these additional cyclic loads. The aim is to improve the fatigue endurance of the martensitic stainless steel materials used in the turbine blade root in a fully predictable/tailored fashion. This will require consideration of the effects of practical heat treatment (tempering) procedures applied during manufacture and assessing approaches for improving the fatigue endurance in specific locations in the blade root using predictable and effective surface treatments that do not materially affect the shape of the component. This requires developing a full understanding of how microstructural optimisation in these systems can improve fatigue resistance - and also the prediction of fatigue mitigation approaches such as shot peening in the complex loading gradients produced by the service notch features. The development of validated fatigue lifing predictions that can be applied easily to in-service surface conditions and appropriate notch geometry measurements in critical stress locations is a key deliverable.