The PreMANI project dealt with predictive manufacturing: design, development and implementation of Digital Manufacturing solutions for Quality Prediction and Intelligent Maintenance. The project started in November 2017 and closed in December 2020.
Objectives
The project has developed innovative techniques to address the issue of predicting the operating characteristics of machines and plants, combining the analysis of product quality with that of plant efficiency, in a context that is therefore described as Predictive Manufacturing. The solutions developed belong to the Digital Manufacturing field, involving the creation of advanced tools for decision support, and components at hardware level (dedicated sensor architectures, low-cost embedded systems for the real-time use of complex prediction models), infrastructural level (cloud-based IT platforms), and algorithmic level (with particular emphasis on the use of machine learning techniques).
The quality of application of the enabling technologies is high, given the breadth and diversity of the application areas considered in the project, which makes it particularly challenging. In fact, the industrial sectors considered represent paradigmatic examples of operating contexts in which ever greater intelligence ("smartness") is required of individual machines that must operate in interconnected environments (mechanical-textile, packaging, precision machining), and of complex and articulated processing systems (foundries, large-scale industrial production, food production systems).
Funding and Partners
The project was co-financed thanks to the Veneto Region's POR Call for Proposals see details for the support of Research and Development projects developed by Industrial Districts and Regional Innovative Networks (Dgr n. 1139 of 19 July 2017). The amount of support obtained by the Premani project as a whole is € 2,999,858.64. The innovative networks involved are RIR IMPROVENET (ICT for Manufacturing Processes Veneto Network) and RIR SINFONET (Smart and Innovative Foundry Network). In addition to IRS, the partners involved are the University of Padua, the University of Verona, T2i - trasferimento tecnologico innovazione Scarl, Electrolux Italia SpA, Galdi Srl, Cielle Srl, Smit Srl, Sordato Srl, Edalab Srl, Simnumerica Srl, M3E Srl, M31 Italia Srl, Statwolf Data Science Srl, Fonderia Corrà SpA, Rds Moulding Technology SpA, Zanardi Fonderie SpA and Enginsoft SpA.
In detail, those related to I.R.S. Srl for the Industrial Research Project foresees an admitted expenditure of €273,863.89 and an admitted contribution of €164,318.33 and a funding for the Experimental Development Project carried out by small and medium enterprises (SMEs) which has an admitted expenditure of €48,682.79 and a contribution of €19,473.12.
