Not long ago, Eduardo Oslé was telling us in this blog how numerical simulation had affected the aeronautics sector, and how terms manage sometimes to express concepts that become innovation.
The term phygital has been coined recently to refer to the possibility of interacting with people in the physical and digital environments, not as the result of an accumulation of anonymous data, but reflecting that we inexorably live two parallel lives in the two worlds because the technological advances and the IoT all converge to a single reality..
Can this term promote innovation? As usual, the answer is “it depends”. The term is starting to be used in areas of marketing and communications, focused on people (QR codes, interaction in social networks, TV by hashtags, etc.), but its main applications remain unexplored.
In the area of simulation software, we have for some time being using the term “digital twin”, mainly in the design stage of new equipment or products by collaborative improvement
However, the prospects go far beyond: machines, under the Industry 4.0 paradigm, incorporate new connectivity and instrumentation technologies which, together with enhanced computation capabilities and the development of cloud platforms, make it possible to combine operational data in real time with virtual simulation performed on the digital twin.
This behaviour, simulated in the digital environment and combined with data from the operation of a machine, will allow us to fine-tune and optimise its performance. Increasingly, we will need virtual assistants and connected devices to control the activity of machines and equipment.
Going back to the previous question: in a paradigm change leading to a true digital transformation in which the focus is not just on technology, the role of the IoT, the cloud and the collaborative platforms will be key for developing the new phygital reality, in applications such as intelligent packaging, digital transformation of factories within Industry 4.0, and in detecting behavioural patterns of equipment using data-science tools.