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Chiara Spirito
Artificial Intelligence applications in Reverse Logistics, how technology could improve return and waste management creating value.
Rel. Giulia Bruno. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2024
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Abstract: |
The research and the analysis will focus on applications of artificial intelligence in the field of “Reverse Logistics”. The activities included in reverse logistics processes cover the product journey from the end user back to the manufacturer with the purpose of reselling, repairing, refurbishing or recycling the item in a circular economy perspective. The purpose of this document is to provide possible answers to the question of how to improve current processes with the help of artificial intelligence to become faster, reduce the number of unrecognized items, improve accuracy, and help generate value for the environment and businesses. An analysis of key technologies and trends will be developed and, considering the different stages of the process, suggestions on possible improvements will be highlighted. Businesses that stand to benefit from these opportunities include those involved in managing returns from e-commerce transactions, as well as those engaged in waste collection and broader recycling operations. An analysis on the industrial interest based on experts’ interviews will be conducted to explore the contribution that AI could bring to current operations in different industries, investigating level of knowledge and applicability of the technology. Subsequently, a convolutional neural network model will be created to test the benefits that technology could enable in a context of waste management in terms of time reduction and accuracy. Finally, a comparison between manual and automated processes in the assessment of waste categories will be developed, highlighting the value that a machine learning algorithm could generate in cooperation with human operators. |
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Relatori: | Giulia Bruno |
Anno accademico: | 2023/24 |
Tipo di pubblicazione: | Elettronica |
Numero di pagine: | 111 |
Soggetti: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management) |
Classe di laurea: | Nuovo ordinamento > Laurea magistrale > LM-31 - INGEGNERIA GESTIONALE |
Aziende collaboratrici: | NON SPECIFICATO |
URI: | http://webthesis.biblio.polito.it/id/eprint/31999 |
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