Ball-nose end-milling process is considered as one of the vital metal removal processes for aerospace pieces. The product surface quality highly depends on how this process is performed. One of the factors that affect the resulting surface roughness is the performance of the ball-nose cutter used. However, this performance changes with the degradation of the tool. Therefore, several tool preparation methods are applied to increase tool life. Old tools seriously damage the surface. To prevent this, it is advised to use tools up to a certain level of damage.

This paper describes the use of vibration analysis with a fully automated diagnostics system to detect common machine faults such as imbalance and misalignment as well as bearing and gearbox faults of offshore machines. Other faults types, e.g. when a large object hits the propeller blades may be detected using the STFT. As the mechanical properties of the structure can change because of changes of temperature and oil quality, these (and other) state data are also stored. The data fusion process is currently under work.

The use of condition monitoring (CM) in wind energy machines continues to evolve as wind energy machines grow in size and move offshore. Early and smaller wind generation machines offered little financial incentives for condition monitoring, justifying only simple and inexpensive health monitoring technologies. Today, multi-megawatt wind machines are more complex, more difficult to physically reach, and generate more revenue than previous models. This paper reviews challenges and candidate technologies for next generation condition monitoring in Wind Energy.

Distributed wireless architecture for prognostics is an important enabling step in prognostic research in order to achieve feasible real-time system health management. A significant problem encountered in implementation of such architectures is power management. In this paper, we present robust power management techniques for a generic health management architecture that involves diagnostics and prognostics for a system comprising multiple heterogeneous components.