Anyone looking for images of the smart factory today will always come across the same motifs: long production lines lined with robots and driverless transport systems that independently transport material to the downstream production step. This image of the factory devoid of people has now become firmly established as a symbol of intelligent production. It is therefore not uncommon for the automation of production processes to be equated with the digital transformation of manufacturing. But is this even true? And what does automation have to do with digitalization anyway?

When cobots were still called hybrid assembly systems ...

The simple answer is: relatively little. This becomes clear when it comes to the topic of "collaborative robotics". So-called cobots, regularly used as a prime example of the smart factory, have been a more or less integral part of modern production systems for over 20 years - long before the term digital transformation first made the rounds. The only difference was that back then they were still called hybrid assembly systems and were programmed using wired handhelds instead of tablets. This form of robotics has nothing to do with digitalization in the sense of automatic manipulation of objects by machines of any kind. Or to put it simply: a high degree of automation alone does not make a digital factory.

Dimensions of digitization

The somewhat more complicated answer is that industrial digitalization encompasses more than just measures to increase efficiency within the smart factory. Overall, three dimensions of digitalization can be distinguished:

1. use of digital tools to leverage additional potential with regard to increasing efficiency in the factory and to exploit things that can no longer be exploited with lean alone.

2. digitalization in the context of new, disruptive business models with changed value chains, customer segments and market development techniques to open up new market shares.

3. and finally, smart products equipped with appropriate sensor technology, storage options and connectivity, which are both transmitters and receivers of information, network with each other and thus enable completely new product features, such as autonomous driving.

The connecting element in all three dimensions of digitalization is not the use of specific technologies, but rather the acquisition, processing and use of data to achieve a competitive advantage in the respective digitalization context. Or to put it the other way round: digitalization does not require robots, but data.

Infrastructure as a prerequisite

In terms of the smart factory, this means that when we talk about digitalization, we first need some kind of extended infrastructure in the form of a communication network, sensors and IT systems for storing and processing data. Digitalization measures can therefore never take place in complete isolation, but require a more far-reaching development plan and should be embedded in an overall strategy. For example, if a company wants to use predictive maintenance analyses as part of its injection molding production, it should first answer questions such as: "Do I even have systems where predictive maintenance makes sense? Where can I achieve my goals better than before and how can I introduce these measures?"

This means that the introduction of digital technologies such as predictive analytics or digital assistance systems differs significantly from the implementation of individual automation modules, such as investing in a robot. As no additional infrastructure needs to be provided here, these steps can be carried out completely independently of each other, whereas in the core area of digital transformation, the measures build strictly on each other.

5 levels of the Smart Factory

In order to better understand how the various aspects of digitalization interact in the smart factory and how certain technology components are to be located, it is therefore helpful to systematically present the various levels of digitalization in the smart factory. This comprises a total of five levels:

Level 0 - Connectivity:
Describes connectivity as the basis for networking objects such as machines, sensors, etc. in the smart factory. It forms the basis for all further stages of digitalization.

Level 1 - Information:
Describes the extraction and presentation of information from these networked objects, for example in the context of reporting, benchmarking, etc.

Level 2 - Knowledge:
Describes the extraction of knowledge from this information, for example to support troubleshooting in the event of a production system failure.

Level 3 - Prediction:
Describes the use of this information to predict certain events, such as the failure of a machine, and to derive specific instructions for action.

Level 4 - Autonomy:
Describes fully autonomous control, in the sense of autonomous control loops, without manual intervention.

All digital technology modules can be placed in this basic system of the digital factory and corresponding application options can be derived. It therefore serves as the basis for further exploration of the smart factory. In the next episode, find out how artificial intelligence is changing the smart factory and how far technology has actually progressed in this area.

Prof. Dr.-Ing. Werner Bick, Chief Representative of ROI Management Consulting AG and Professor at OTH Regensburg / ag