There is little consensus about the term Industry 4.0 among champions of its various initiatives. However, stakeholders commonly envision that connected factories and services will revolutionize manufacturing, as did machinery, electricity, and information technology. Industry 4.0 technology often features machines, parts, and services that exchange data and self-configure to support both dynamic and agile manufacturing processes.

The German Research Centre for Artificial Intelligence (DFKI) has played key roles in managing and participating in research programs that are associated with the Industry 4.0 concept. It cofounded the nonprofit SmartFactory in 2005 and has hosted the initiative since 2011. Semantic technologies have played an interesting role in DFKI's research on manufacturing; for example, equipment reads and interprets tags (some researchers refer to them as forms of semantic product memory) that are embedded in workpieces and that trigger subsequent manufacturing processes. Related research at DFKI seeks to enable machines to diagnose themselves when issues arise and to provide explanations of malfunctions that humans can read and understand. Several other Industry 4.0–related research centers, including labs within some Fraunhofer-Gesellschaft institutes, seek to exploit AI technologies.

Implications

Organizations in Germany aim to supply Industry 4.0 technologies to a global base of customers and are consequently engaged in efforts to set industry standards. The Industry 4.0 concept originated in Germany, and sources of related research funding appear to be concentrated there. Google Trends indicates that searches for Industrie 4.0, the German-language term, greatly outnumber searches for Industry 4.0 (the English term). Searches for Industrie 4.0 are highly concentrated in Germany and Austria, whereas searches for Industry 4.0 are concentrated in Germany and Japan.

Impacts/Disruptions

"Industry 4.0 does not mean production without people," according to a December 2014 BMW Group press release; indeed, many affiliated research projects focus on human-machine collaboration, especially on context-sensitive computing. Significantly, from 2010 to 2012, DFKI led the EU-funded Cognito project. Making use of computer vision, Cognito systems recognized patterns that were generated by body-mounted sensors to examine the dynamics between human workers and workpieces. For example, a worker would be alerted when an anomaly or some other condition called for a change in workflow. Generally, advanced implementations of context-sensitive computing need to recognize user intentions with minimal to no explicit user input—a goal that fits squarely in the domain of AI research.

The use of AI may be a significant factor in efforts to innovate manufacturing processes under the Industry 4.0 banner. Some other research themes associated with Industry 4.0 include cyber-physical systems, the Internet of Things, machine-to-machine communications, RFID, and robotics; such innovations seem to already pervade manufacturing in many developed countries. Still other Industry 4.0 research themes, such as augmented reality, are common in advanced manufacturing R&D worldwide. In contrast, a relatively strong emphasis on integrating AI technologies into industrial processes seems to distinguish Industry 4.0 efforts at research institutes and large companies in Germany (as well as a few other European organizations) from advanced manufacturing efforts elsewhere.