EIT Digital is introducing its’ I4.0 Production Monitoring Solution‘,a new initiative launched as part of its Oedipus High Impact Initiative, and designed to help manufacturers quickly assess whether their machines are performing well or need some fine-tuning.
This new modular solution, conceived and developed by the Italian’digital innovation and design shop’ Cefriel, is designed to work both with older, non-natively connected machinery, and with newer models that are equipped with Internet connections.
“We will be able to retrofit amachine by connecting it with an external IoT board. Sensors will collect relevant data such as temperature or vibration levels, to provide precious insights on the equipment’s condition.The information gathered will be exported to Siemens’ MindSphere cloud platform, which is specifically designed to monitor industrial plants,”Nadia Scandelli, Cefriel’s Deputy Head of Digital Platform says.
This retrofitting process could be potentially very attractive for factories, as it is relatively inexpensive compared to replacing the equipment altogether with newer, smarter models, somethingwhichmanufacturers tend to avoid or delay due to the high cost of investment.
If the machines already support Internet connectivity, of course, the boards are not needed, and clients will be able to skip this part of the solution and focus on data visualization aspects to monitor performance.
“We have already connected our board to MindSphere, now we are creating an ad hoc dashboard allowing managers and factory workers to access thisdata in a less technical and more easily understandable way’, Scandelli explains.
Potential customers of Cefriel’s product could either be companies that want to update their ’dumb’ machines with new capabilities that will allow them to remotely monitor the performance and status of those machine, without incurring too many expenses, or manufacturers who produce connected machine tools and want to sell (or provide as a free bonus) an analytics service on top of their current offerings.
Employees of the internal R&D departments of the machine producers could also be interested in the data analytics part of the solution, as it’s of the foremost importance for them to understand how theirmachinesarebeing used.
“We expect having a first minimum viable product ready by the end of the year,” Scandelli says.