"Industry 4.0," or digitization of production sites, has become a routine factor in business and industry. The next step in this overall trend is called "industrial intelligence."
Hannover Messe 2019, this year's edition of Hannover's industrial trade fair, will soon be getting underway. In the run-up to the trade fair, I've been spending some time considering the latest technical terms being applied to the development of the industrial sector as a whole. In the process, I've been focusing on the terms "Industry 4.0" and "industrial intelligence," especially with regard to how they relate to one another.
I started with the term "Industry 4.0." In Industry 4.0, production and logistics processes are broken down into digitalizable sub-processes, on the basis of precise analysis. Such techniques are used, for example, to create networks of production sites. Production sites in such networks are able to plan and deploy their resources more efficiently than they otherwise would. They then also become better able to adjust to changes in order situations.
The key basis for creation of networked production sites is the Internet of Things. In smart factories, all kinds of devices are connected to the Internet. And they communicate automatically. So far, so good. But what does this have to do with industrial intelligence?
Industrial intelligence – the successor to Industry 4.0
The "4.0" in "Industry 4.0" tells us that we're talking about the latest industrial revolution. Industry and technology keep changing and developing. So we know something will come after Industry 4.0. But what? Here's where "industrial intelligence" comes into play. Industrial intelligence is being touted as a hot candidate – and not only at the Hannover Messe trade fair – for the role of successor to Industry 4.0.
Industrial intelligence refers to use of artificial intelligence (AI) in industry. In particular, to use of "weak AI." Weak AI enables machines to perform certain carefully defined tasks, by giving them narrow sets of human-like abilities. Tasks such as speech recognition or image recognition. In an industrial context, weak-AI development focuses especially on equipping machines to process large quantities of data and on designing complex machine processes.
Such complex processes can include maintenance processes. In industry, any instance of machine failure or production downtime can be expensive. For this reason, Predictive maintenance is now playing a vital role.
Industrial intelligence in service
Predictive maintenance involves use of artificial intelligence. Integrated sensors in machines generate enormous quantities of data. Increasingly, their data are being evaluated with the help of AI systems. Such systems alert operators as soon as machines exceed defined parameters or thresholds. In so doing, they can prevent machine failures.
We should also note that real-time transmission of the enormous quantities of data required for predictive-maintenance processes calls for excellent network connections. And for suitable cloud-based computing capacities. Campus networks are computer networks for limited geographical areas, such as those occupied by factories or industrial complexes. Such networks are already in service for new applications, such as systems of autonomous, networked vehicles that transport material throughout production sites. In the future, the industry will be able to further automate its processes with the combination of a 5G campus network, cloud and artificial intelligence.