Industrial transformation

If we take a closer look at individual sectors of industry and markets, we can see increasing volatility even within these ecosystems, for example in the automotive or electronics sector. Industry must find solutions that can flexibly deal with these fluctuations.

“Made in Germany” and German engineering expertise still enjoy an excellent reputation the world over. Our capital is profound expert knowledge in the construction of machinery and systems and in industrial production processes. Industry 4.0 initiated the fusion of state-of-the-art information technologies with the manufacture of machinery and production systems. We are now in the midst of an industrial transformation from large-scale series production to individually customisable products down to batch size 1.

With its smart digital solutions, the automation expert Festo is blending its comprehensive expertise in industrial applications with current developments in information technology, in order to realise software applications for industrial practice in automation. In digital communication, Festo accompanies its customers on the Digital Customer Journey, which securely and comprehensively leads them through the performance portfolio of Festo – from the acquisition of information and configuration, through ordering and delivery, up to commissioning and maintenance.

This is all now being supplemented by the skills and methods from the toolbox of artificial intelligence (AI). For the first time, they are enabling us to derive data directly from machinery and industrial production systems in operation by means of appropriate sensors, so that we can evaluate these data in real time and thus round out our knowledge of dependencies and interactions in the manufacturing process. Thanks to digitalisation and AI, the complexity of these processes is becoming fully controllable.

AI is the key to the world of tomorrow

The German government has defined the framework and the aims in its AI strategy: Germany should consolidate its strong position in Industry 4.0 and assume leadership for AI applications in this field. SMEs in particular are to benefit from these AI applications.

We are focusing on transferring our core competence of factory automation to the AI-supported, digitalised production of tomorrow. Today, algorithms analyse the data from machinery and provide forecasts of failures or prevent them from occurring. Tomorrow, algorithms will monitor, control, navigate, supervise and regulate value flows in a complex network. While they will not replace decisions by humans, they will support them in their decision-making.

The classic automation pyramid, with a linear connection between the production and corporate levels, is dissolving and is now orienting its structure towards networked, synchronised production. At the same time, digitalisation is generating virtual twins of machinery, systems and value flows. The great advantage here is that processes, parameterisations and configurations can be acted out in these computer-generated simulations without the need to intervene in existing production processes. Setting-up time and downtime are reduced. This saves costs and time – which is crucial for countries with a high labour content in manufacturing costs, so that they can remain competitive on the global market.

“High productivity due to full automation makes stockpiling of many spare parts necessary, for example, and gives rise to high personnel costs in preventive maintenance. AI, and here in particular machine learning with anomaly recognition, will help reduce these costs in future”, said Dipl.-Ing. Dr. h.c. Oliver Jung, Chairman of the Management Board of Festo AG.

Making good use of AI

To generate added value and increase efficiency with the methods from the algorithmic toolbox, use cases must be precisely defined. Satisfactory results are only possible if the data are strategically prestructured and are available in sufficient quantity. “We have taken a close look at quality assurance with AI in a production process at our own factories and have come to the conclusion that the big data approach from the consumer market is not successful in industry. We only managed to significantly increase efficiency once we united the expertise of the machine operators with the appropriate statistical methods of AI”, said Oliver Jung.

Festo is currently focusing above all on AI assessments “on edge”, in other words directly on the component, or on location within a production network. This saves costs, ensures real-time assessments and avoids latencies. Only intricate evaluations involving production locations distributed throughout the world need the large computer capacities of a connected Cloud infrastructure.

With the Festo IoT Gateway, existing production plants can be made AI-capable without major intervention. Algorithms and models can be updated directly on a device without modifying the PLC, independently of the computer capacity or the free resources of the PLC.

From mechanical to smart products

With the Festo Motion Terminal VTEM for example, Festo has already paved the way for digitalised pneumatics: the functions of the valve terminal can be controlled by app, so that different tasks can be carried out with the same hardware. In sectors of industry that manufacture products strongly oriented to individual customers’ wishes, such as kitchens, the potential degree of automation therefore rises.

What does this mean for people?

As the innovation leader in factory and process automation, Festo always focuses on people in addition to technical solutions and sees the role of technical education and training as crucial both to technological innovation and to promotion of the labour market.

Already in the 1950s, Festo realised that new technologies can only develop their potential when people know how to deal with them, and as a result founded Festo Didactic SE. As a global partner to educational institutions, governments, state-run facilities and companies throughout the world, Festo Didactic SE establishes and maintains training centres and laboratories as well as integral learning solutions and training programmes that systematically prepare people for working in dynamic and complex environments.

“Vocational training is thus a key to a company’s competitiveness”, emphasises Oliver Jung. The workplace is therefore becoming a place of “lifelong learning”. Companies rely on constant learning on the part of their employees to maximise their productivity. Self-controlled learning, and learning in contexts of application, are also gaining significance. With digitalisation, the competence required in both existing and new professions will continue to change, and with it also the requirements on education and training.