Analytics and Methods for Logistic System Design and Operations Management

Tufano, Alessandro (2021) Analytics and Methods for Logistic System Design and Operations Management, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Meccanica e scienze avanzate dell'ingegneria, 33 Ciclo.
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Abstract

Analytics is the technology working with the manipulation of data to produce information able to change the world we live every day. Analytics have been largely used within the last decade to cluster people’s behaviour to predict their preferences of items to buy, music to listen, movies to watch and even electoral preference. The most advanced companies succeded in controlling people’s behaviour using analytics. Despite the evidence of the super-power of analytics, they are rarely applied to the big data collected within supply chain systems (i.e. distribution network, storage systems and production plants). This PhD thesis explores the fourth research paradigm (i.e. the generation of knowledge from data) applied to supply chain system design and operations management. An ontology defining the entities and the metrics of supply chain systems is used to design data structures for data collection in supply chain systems. The consistency of this data is provided by mathematical demonstrations inspired by the factory physics theory. The availability, quantity and quality of the data within these data structures define different decision patterns. Ten decision patterns are identified, and validated on-field, to address ten different class of design and control problems in the field of supply chain systems research.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Tufano, Alessandro
Supervisore
Dottorato di ricerca
Ciclo
33
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Analytics, Logistics, Operations, Machine learning
URN:NBN
Data di discussione
26 Marzo 2021
URI

Altri metadati

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