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A Machine Learning approach to Predictive Control: study on a real industrial application

Hajjoubi, Abdeljalil

A Machine Learning approach to Predictive Control: study on a real industrial application.

Rel. Elena Maria Baralis, Sophie Fosson, Rosaria Rossini. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2018

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Abstract:

The aim of the thesis is to build a system of data collection and analysis, through the integration of a distributed storage and processing system and machine learning techniques, at a small scale. A dataset of industrial data is available for predictive control analysis. Specifically, the dataset contains historical time series of several parameters regarding a manufacturing process, annotated with breakdowns. Our goal is the develop classification strategies that identifies the conditions that cause a breakdown, exploiting Machine Learning tools. Hadoop and TensorFlow, or analogous softwares could be used.

Relatori: Elena Maria Baralis, Sophie Fosson, Rosaria Rossini
Anno accademico: 2017/18
Tipo di pubblicazione: Elettronica
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA
Aziende collaboratrici: Istituto Superiore Mario Boella
URI: http://webthesis.biblio.polito.it/id/eprint/7572
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