Facoltà: Ingegneria Gestionale - classe LM-31
Collocazione: 19951
Autore: Coscia Vanoni Marco
Data: 20/12/2021
Titolo: Adoption model of Data Science techniques and tools to support Lean Production practices: a case study research
Relatore: Pozzi Rossella
Autorizzazione per la consultazione: NO
Le tesi si possono consultare unicamente in sede
Data Science is one of the most debated topics in the academic field and in which companies oriented to continuous improvement have many expectations. In addition, the literature has shown that the technologies available to understand phenomena through data analysis can effectively improve the results of Lean practices. The evidence of a link between Data Science techniques and tools and Lean Production practices emerges, in particular, from the analysis of the existing literature and recent scientific publications. However, the link between these two topics is still underinvestigated. The main gap is identified by the lack of examples of empirical validation of Data Science techniques and tools to support Lean Production practices and the practical application of adoption models. Moreover, no attempt to understand the critical success factors for Data Science techniques and tools implementation to improve Lean Production practices and the barriers that can threaten this implementation can be found in the literature. This research dissertation describes initiatives adopted by six cases involving Italian plants or international companies located in Italy through an exploratory, qualitative research methodology and a cross-case comparison. Initially, the literature analysis will be presented regarding the link between Data Science and Lean Production practices, Critical Success Factors, and Barriers related to implementation projects. The research methodology is based on direct interviews of the use cases and they will then be described. After the companies' reports, the discussion part analyzes the data obtained through interviews, answering the research questions presented in the first chapter of the paper.
