Sviluppo di una linea intelligente per il converting della carta tissue: le tecnologie ICT al servizio dell'Advanced Automation
Funded by: POR CREO FESR Regione Toscana 2014-2020
Start date 1 December 2017 End date 14 July 2020
Keywords: Augmented Reality; Artificial Intelligence; Computer Vision; Industry 4.0; Predictive Maintenance; Smart glasses
Tissue converting lines represent one of the key plant in the paper production field: with them, paper tissue is converted into its final form for domestic and sanitary usage. Despite the actual lines have yet high productivity, the study of the state of the art has shown that bottlenecks still exist, mainly depending on inadequate automation. IRIDE aims at removing such obstacles towards the complete automation, by introducing a set of innovation points based on ICT solutions applied to the advanced automation.
In detail, advanced computer vision and video analytics methods will be applied to pervasively monitor converting lines and to automatically extract process information to self-regulate machine and global parameters. Big data analysis methodologies will be also integrated to obtain new knowledge and to infer optimal management models that could be used for predictive maintenance.
Augmented reality interfaces will be designed and developed to support converting line monitoring and maintenance, both ordinary and extraordinary. An Artificial Intelligence module will provide suggestions and instruction to the operators to guarantee production level even in the case of unskilled staff.
Thanks to the new sensor equipment, advanced automation aspects will be linked with tissue drawing-in and production line cleaning. The automation of such processes will improve factory safety, decrease manual interventions and, thus, will increase production line uptime and efficiency.
Signals and Images Lab role in IRIDE Project
The research team of the Signal and Images Lab involved in IRIDE project focused on:
- Study and development of image-based methods to monitor the converting process and detect faults and anomalies;
- Augmented reality solutions for Industry 4.0;
- Intelligent systems and decision support for predictive maintenance.