The Internet of Things technology was front and center in the second event of the cycle named I4.0@DEIB, held at Politecnico di Milano: a debate about an important change of perspective on the transformation towards the interconnected factory, based on the possibility of collecting and analyzing production data and involving the whole supply chain, including end users.
by Fabrizio Dalle Nogare
The Internet of Things (IoT) is a technology that allows objects to become recognizable, communicate data about themselves and access information in turn. Industrial applications are among the main outlets of such a technology, so much so that we talk about the Industrial Internet of Things (IIoT).
The Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano – among the liveliest academic institutions, not only at national level, on this topic – promoted an event that involved representatives of university, IT multinationals and
manufacturing companies. “The advent of Cloud services has undoubtedly given the IoT a boost – said Professor Matteo Cesana from DEIB – and led to the development of smart devices, equipped with sensors, that can be found on the human body (let’s think of wearable devices) or on the machines. Rather than interconnecting factory systems, the IIoT aims to facilitate the acquisition and exchange of data”.
For sure, according to Professor Cesana, the complexity of the scenarios that the IoT involves implies an ever stronger synergy between universities and companies.
Important changes, from maintenance to R&D
For this reason, some representatives of both IT and manufacturing companies discussed the topic and set out their points of view also during a round table in the final part of the event. “There is an increasing need for training today, also to be able to manage the huge amount of data generated by objects: the fact of collecting data by itself does not guarantee any added value. These data are rather supposed to generate some benefits”, explained Andrea Benedetti from Microsoft. “Microsoft’s IoT suite, Azure, is designed to be secure, fast, open, and scalable”.
Alberto Olivini from Siemens, a company that developed a platform named Mindsphere, focused its speech on the potential of the IIoT in production digitalisation. “What benefits can a machine builder get from the IIoT? Improving maintenance and offering services that were previously unthinkable or giving, for example, indications to the end customer, in real time, on the condition of a machine. But it is also possible to create new business models and influence R&D”.
Possible developments and obstacles to overcome
Luca Arduini from SuperMicro, an American company working in the field of IT storage, focused on the development of hardware systems for Cloud and IoT, introducing a technology that is an alternative option to cloud, i.e. edge computing: a set of devices that, locally installed, allow users to implement data analysis, in fact, at the local level.
The point of view of Bosch Rexroth, represented at the conference by the IIOT Specialist Andrea Damiani, is that of a group that manufactures internally many of the technologies that enable Industry 4.0. The company relies on the concept of distributed intelligence, defined by Damiani as “an idea that includes not only electronic components, but also the integration, for example between operators and AGVs. A concept that embraces, in short, also and mainly the people”. Alfredo Drago from Ansaldo STS provided the point of view of a manufacture of rail transport systems, which uses technologies such as the IoT. “The application of the IoT on trains allows, for example, for real-time monitoring of any component in order to check its status”, he said, adding a short list of aspects that may hamper the application of the IoT. Starting from the sometimes high cost of the implementation of data collection methods, at least in the railway sector, up to issues such as security, availability of data or finally the difficulty in finding those figures – let’s think of data specialists – who might analyze data in order to generate added value.