Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
INDUSTRY 4.0 CAPACITY BUILDING THROUGH DESIGN & ENGINEERING COMPETENCE. AN EXPLORATIVE STUDY ON AI INTEGRATION IN TUSCAN TEXTILE SMES
Goretti, Gabriele; Mazzei, Daniele; Dastoli, Caterina; Masini, Lorenzo
Type:
Year:
2025
Editor:
Bohemia, Erik; Buck, Lyndon; Grierson, Hilary
Author:
Series:
E&PDE
Institution:
DESTEC Department, University of Pisa, Italy; Computer Science Department, University of Pisa, Italy; Supermateria Srl
Page(s):
379 - 384
DOI number:
ISBN:
3005-4753
ISSN:
978-1-912254-22-4
Abstract:
The integration of Artificial Intelligence in manufacturing is increasingly shaping digital production and consumption models, enabling companies to optimize strategies and operations across the production-consumption continuum. In the context of textile manufacturing in Italy, this study examines AI capacity building within advanced craft-based enterprises. Specifically, it explores how design and engineering academics can facilitate the adoption of AI in the production and consumption systems of Tuscan Small and Medium Enterprises. This research focuses on a preliminary workshop organized by the University of Pisa in collaboration with selected Tuscan textile manufacturers. The workshop aimed to introduce companies to the potential of AI in production processes, offering creative methods and simulations applicable to their organizational contexts. A key focus was the simulation of AI integration throughout the textile supply chain. To enhance the development of insights, the authors provided participants with a structured instructional model. Drawing on the double diamond framework as a reference design approach, the model incorporated methods traditionally employed in design thinking. By examining this initiative, the paper highlights the role of academia in fostering AI-driven innovation within traditional manufacturing sectors, demonstrating how structured Design methodologies can support SMEs in navigating digital transformation.
Keywords:
