ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-03262012-183320


Tipo di tesi
Tesi di dottorato di ricerca
Autore
ILIANO, SALVATORE
URN
etd-03262012-183320
Titolo
Tecniche di augmented reality nella conduzione e manutenzione dei sistemi di produzione
Settore scientifico disciplinare
ING-IND/16
Corso di studi
INGEGNERIA MECCANICA
Relatori
tutor Prof. Dini, Gino
relatore Prof. Failli, Franco
Parole chiave
  • sistemi di produzione
  • augmented reality
  • training
Data inizio appello
17/04/2012
Consultabilità
Completa
Riassunto
Augmented Reality (AR) is an innovative technology which allows superimposing, to the normal reality perceived through our senses, information and virtual objects computer-generated and displayed on specific devices (e.g. Head Mounted Display).
Maintenance, control and management of complex systems, such as machine tools with numerical control or flexible manufacturing systems, has significantly increased the level of skill and experience required to operators who act in such systems, making it crucial for a company to provide them adequate training.
Training is an area that, for its characteristics, makes it advisable the use of AR. The operator is guided step by step in performing the various operations composing the task that he has to perform, thus working in complete safety and obtaining a standardization of the training that is not available with the classic on-the-job training method.
In this PhD thesis it is described the research aimed to study the applicability of AR technology to training and support of workers within production systems in order to improve the human-machine interaction.
Topics related to the practical implementation of AR technologies, the interaction of the operators with suitable devices, i.e. possible hardware configurations and modes to convey information, have been deeply analyzed, and various applications have been realized in the field of production systems.
In conclusion, it was investigated the integration between AR and wireless sensor networks for operator feedback.
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