Alessandro Beghi

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In this paper, a multiple classifier machine learning (ML) methodology for predictive maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating the so-called “health factors,” or quantitative(More)
Nowadays, the adaptive optics (AO) system is of fundamental importance to improve the real resolution of ground-based telescopes. In practical applications the telescope resolution is limited by the atmospheric turbulence. The aim of the AO system is that of estimating the atmospheric turbulence and computing a suitable input for a set of deformable mirrors(More)
The phase screen method is a well-established approach to take into account the effects of atmospheric turbulence in astronomical seeing. This is of key importance in designing adaptive optics for new-generation telescopes, in particular in view of applications such as exoplanet detection or long-exposure spectroscopy. We present an innovative approach to(More)
Simulating the turbulence effect on ground telescope observations is of fundamental importance for the design and test of suitable control algorithms for adaptive optics systems. In this paper we propose a multiscale approach for efficiently synthesizing turbulent phases at very high resolution. First, the turbulence is simulated at low resolution, taking(More)
Silicon Epitaxial Deposition is a process strongly influenced by wafer temperature behavior, that has to be constantly monitored to avoid the production of defective wafers. A Predictive Maintenance (PdM) System is here proposed with the aim of predicting process behavior and scheduling control actions in advance. Two different prediction techniques have(More)
In semiconductor manufacturing, state of the art for wafer quality control relies on product monitoring and feedback control loops; the involved metrology operations are particularly cost-intensive and time-consuming. For this reason, it is a common practice to measure a small subset of a productive lot and devoted to represent the whole lot. Virtual(More)
Recently developed optimization and nonlinear control strategies are applied to drive a multi-body motorcycle model along a specified path with an associated velocity profile. The resulting control scheme is based on three main pillars: a dynamic inversion procedure to compute the input-state trajectories corresponding to a desired maneuvering task, an(More)