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Artificial Intelligence for Smart Manufacturing

keywords INDUSTRY 4.0, MACHINE LEARNING, AI

Reference persons GIULIA BRUNO, MANUELA DE MADDIS

Research Groups Gestione della conoscenza nello sviluppo prodotto/processo

Thesis type EXPERIMENTAL RESEARCH

Description Smart Manufacturing (SM) can be defined as the extensive application of computer-integrated manufacturing and advanced intelligence systems to enable rapid manufacturing of new products, dynamic response to product demand, and real-time optimization of manufacturing production and supply-chain networks. The aim of SM is to respond to demand-dynamic economics, variability management, real-time materials engineering, and broad-based workforce involvement, thus reflecting the magnitude and impact of the smart technologies of the Industry 4.0 paradigm.
Today, the amount of data generated continues to grow exponentially along with the digitalization of information, and the use of the Internet of Things (IoT) within factories (IIoT) to such an extent that manufacturing is identified as one of the five domains in which Big Data has transformative potential. For this reason, SM is now attracting a huge amount of interest in both academic and industrial communities, and will probably drive the manufacturing evolution in the next decade.
SM is considered as the evolution of Intelligent Manufacturing (IM), IM being knowledge-based, whereas SM is data-driven and knowledge-enabled. SM uses Artificial Intelligence (AI) techniques to learn directly from data and assist decision making, in contrasts with the "expert system" approach that aims to mimic the rules from human experts with the help of analysts who translate human rules and context expertise into software models.
In SM, AI straightforwardly supports decisional systems and human operators by helping them to improve production and process control, to monitor continuous production flows, to prevent or detect equipment failures at an early stage, to minimize inefficiencies through the overall supply chain, and so on. AI, in fact, combines a wide variety of advanced technologies to give machines an ability to learn, adapt, make decisions, and display new behaviors.

The thesis project includes the following tasks:
Bibliographic research on manufacturing paradigm revolution caused by deep integration of AI techniques with manufacturing technologies;
Bibliographic research on structuring of and algorithms in manufacturing application;
Identification of preliminary case studies;
Execution of the necessary experimental tests, gathering the big data from the process;
Develop and application of Machine Learning algorithms to extracted knowledge and information.

Required skills Basic knowledge on Data acquisition and Data analysis, Statistics, Artificial Intelligence, Manufacturing processes, Methods and tools for the management of production processes.


Deadline 15/03/2021      PROPONI LA TUA CANDIDATURA




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