CYBER PHYSICAL SYSTEM
The synergy between IoT and Big Data technologies is one of the foundations of Cyber-Physical Convergence (and of the corresponding Cyber-Physical Production Systems – CPPS). Cyber-Physical Convergence is defined by a circular process (Information Value Loop) between the physical and the cyber world (Internet). Thanks to IoT technologies, objects and people constantly generate data that passes from the physical world to the cyber world via pervasive networks.
In the cyber world, Big Data technologies make it possible to analyse collected data by extracting knowledge.
It should also be noted that the same focus on the aspects of IoT and Big Data is the basis of the initiative (IDS) led by Fraunhofer in Germany, the main German research institution directed towards industrial innovation. In particular, IDS is seen as the enabling factor for all Industry 4.0 solutions and is focused on the collection, management and analysis of data on the entire production chain, both within the different units of the same company, and within the various companies of the same production chain.
Contextualized in the world of Industry 4.0, Cyber-Physical Convergence allows for a continuous interaction between things, data, people and services, which is the basis of many of the fundamental concepts of Industry 4.0 or Enterprise 4.0.
This interaction allows for that continuous circular process of:
- data production;
- data analysis;
- maintenance and reconfiguration of production processes.
There can be different areas of application of the circular process illustrated above. If it is applied to a single production process, for example, this approach allows you to be able to accurately and continuously monitor the process in such a way so as to constantly improve it over time and adapt it to the variability of the external context (with benefits in terms of costs, time and flexibility of the process in question from a “zero-defect” perspective). If this is extended to different departments and lines of the same company, it will allow for optimal internal integration, thus improving performance at the company level (vertical integration). Finally, if the IoT and Big Data approach were both extended to the value chain, the flow of information on products during their life cycle and on the customers themselves would allow for the company business models to evolve in the direction of offering services with high added value and circular economy.
Given that IoT and Big Data technologies are currently mature (although always evolving in the research sector), it is possible to plan timely and immediate interventions for the adoption of IoT and Big Data technologies right away, with a view to a longer-term migration towards Industry 4.0 models.
By applying these technologies, it is possible, for example, from now on:
- integrate IoT devices for monitoring the various stages of production;
- analyse Big Data from the production process or from the use of products by customers;
- build circular processes according to the Information Value Loop scheme. At the moment it is reasonable to think of implementations in this sense within a single production reality or, in the case of larger companies, as a support for the “vertical” integration of various production units of the same company. One of the most immediate examples of this approach is the predictive maintenance of machinery.