BigData@MA project kick-off

BigData@MA project kick-off

Big Data application at MAnufacturing industry

On July 3 2018, the kick-off meeting of BigData@MA (Big Data application at MAnufacturing industry) project took place in our office in Dalmine (Bergamo, Italy) in the presence of the partners: RINA, TENOVA, Storelink, Centre d’Excellence en Technologies del’Information et de la Communication (CETIC) and Industrial Consulting Research Engineering (I-CARE). The aim is to use new technologies for Big Data analysis in manufacturing production, in particular in mechanics & steel and pharmaceutical industries. This two-years project is co-financed by the European Commission, Lombardy Region (Italy) and Walloon Region (Belgium) as part of the call “MANUNET Transnational Call 2017”.

Today Big Data (BD) technologies are widely applied in sectors outside manufacturing (e.g. finance and telecommunication). Such technologies allow to manage high-dimensional data (pictures, videos, data sensors) associated with complex production processes in order to acquire significant information, to detect plant/process/product anomalies and to provide real time support in decision-making processes.

To extract the full potential of Big Data techniques and apply it to manufacturing production, particularly in complex processes like in mechanical and pharmaceutical industries, adaptations of DB technologies are required. It is necessary to consider the following key aspects: processes with different characteristics (batch, semi-continuous, continuous); complex production lines and machineries working in different plants; wide variety/high quality of products.

BigData@MA project, coordinated by RINA, intends to develop a BD framework, tailored for manufacturing sector, able to handle, in a short available processing time, huge amount of structured and unstructured data. On this basis, real-time analytics tools and predictive models will be developed for maintenance in production line and grinder machines. The proposed solutions will be implemented and tested in industrial environments of mechanics and pharmaceutical sectors.

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