The Premani project

POR FESR 2014-2020 Azione 1.1.4 Networks and Districts

Cielle’s journey toward Industry 4.0 continues with its participation in the PREMANI project funded by POR FESR 2014-2020 to develop an innovative and unique platform capable of improving machining quality and predicting breakages that cause prolonged machine downtime.

After reviewing the statistics provided by our Technical Assistance department, the electrospindle turned out to be the ideal component to start developing this platform since the quality of machining depends on its condition and it is also the one most prone to breakage and the latter leads in most cases to very prolonged machine downtime.

So the decision was to install sensors at some strategic points of a pantograph head to acquire data under different machining conditions and with different materials. This data will be used mainly on two fronts; the first is to develop algorithms that will allow the management software to automatically correct predetermined parameters to ensure that the final product always complies with the quality requirements, and if these actions do not lead to a successful outcome, the software will suspend machining and send a warning output to an operator who will have to intervene to restore production. This function finds its ideal use on machines equipped with an automatic material loading and unloading system, and that work for many hours without operator supervision, thus averting the risk of finding oneself at the end of the process with a high number of scrap pieces that may lead to a loss of several thousand euros.

The second aspect on which we are working is that of predictive maintenance, which consists of predicting electrospindle breakage well in advance, allowing our technicians to intervene in such a way as to avoid prolonged machine downtime that generates a large loss of profit that is difficult to amortize. This function is always avaialble thanks to the reading of data provided by the sensors, through which the parameters established will make sure that the component is working acceptably and beyond which it is advisable to intervene to replace the severely compromised part.
Later on, this predictive function will not only be applied to the electrospindle, but also to other machine parts.

In conclusion, the PREMANI Project leads to the development of platform that will enable our customers to have a tool that can produce consistently high-quality parts for a long time, while at the same time helping to reduce deployment and maintenance costs.

The grant awarded to the PREMANI project by the Improvenet network amounted to €2,999,858.64.

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