BigData@MA intends to develop a specific Big Data application framework as solution to online support decisions tasks in manufacturing sector (mechanic and pharmaceutical). Streaming analytics tools and predictive maintenance models will be then implemented for production chain and machine control in order to detect anomalies and deviations. This framework will be realized by adapting to manufacturing existing Big Data technologies taking in consideration the requirements and constrains of the sector. It will be then tested under real work conditions.
CSM will increase its experience in process data analysis and modeling and enforce its position as regional and transnational reference point in Industry 4.0 Area. Tenova and I-Care intends to exploit the results to enhance the delivery of predictive maintenance models and analytics based on the Big Data framework in the mechanical and pharmaceutical sectors respectively and accelerate full integration of reliability methods into plant management programs. StoreLink will improve its competitiveness on the market in the field of technological innovation and exploit the results in other sectors such as flexible “IoT/Smart Building” and “Cyber Security”. Finally, CETIC objective is to expand its knowledge on industry specific needs for IT tools for BigData.
CSM will develop analytic tools and maintenance models specific for rolls grinding process.
Tenova Pomini, as roll grinding machines manufacturer, will install specific and innovative sensors in a steel plant defined for the final test of the Big Data framework.
Similarly to Tenova, I-Care will test the Big Data framework and related analytic tool/predictive models and exploit the results to enhance the delivery models in the pharmaceutical sector.
Storelink will develop software solutions, based on Big Data techniques, for data visualization.
CETIC target building of a generic data analysis and visualization tool chain for industrial sector deployable on Cloud Computing environments.
The most relevant benefits stemming from the BigData@MA is the exploitation of the full potential of Big Data techniques in the manufacturing production (mechanic and pharmaceutical). Developing a Big Data framework, tailored for this specific industrial sector, will allow a reduction of the operating costs, reduction of maintenance costs, an increase of the annual production and finally an increase of the revenues.