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Salierno, Giulio, (2021)  - I progressi dell’ICT per sistemi ferroviari basati su computer  - , Tesi di dottorato - (, , Universitą degli studi di Modena e Reggio Emilia ) - pagg. -

Abstract: The railway industry's digitalization is enabled by new ICT trends, which significantly impact traditional railway computer-based systems. The work of this thesis covers three aspects related to the digitalization of railways systems at different levels. The first topic introduces formal methods for developing railways safety-critical systems, starting from a relay-based development process. The challenges that emerged from changing the development process model are discussed in the thesis; thus, a methodology for introducing formal methods into an existing development process of an interlocking system is examined. This methodology adopts Statechart models for system design and the Temporal Logic for Actions (TLA+) language for formal verification. The proposed BLExtractor tool produces executable code in the boolean form, starting from Statechart models. The second aspect is related to the characterization of core technologies to enable the “Factory of The Future” in the context of Industry 4.0. The thesis reports a comparison between Virtual Factory, Digital Factory, and Cloud Manufacturing examining paradigms' interoperability, processes, and technologies to enable networked manufacturing. Moreover, a study on QoS loss in cloud service composition for Cloud Manufacturing with the aim to measure a trade-off between QoS optimality and manufacturing constraints on the cloud is included. In addition, the state-of-art applications of agent-based systems are reviewed by studying its maturity for the applicability into the digital factory context. The last topic regards the application of Big Data technologies for the analysis of railway IoT data. The thesis illustrates the Big Data infrastructure that has been built to collect, process, and analyze data produced by objects composing the railway yard. The proposed architecture has been deployed using containers. Experimentations and model evaluations employ data collected from an existing railway line. A failure prediction model is, then, proposed for detecting and predicting failures of railway switch points.